AGI will be embedded into humanoid robots, which makes white-collar and blue-collar jobs a target ... More for walking/talking automation.getty In today’s column, I examine the highly worrisome qualms expressed that the advent of artificial general intelligence (AGI) is likely to usurp white-collar jobs. The stated concern is that since AGI will be on par with human intellect, any job that relies principally on intellectual pursuits such as typical white-collar work will be taken over via the use of AGI. Employers will realize that rather than dealing with human white-collar workers, they can more readily get the job done via AGI. This, in turn, has led to a rising call that people should aim toward blue-collar jobs, doing so because (presumably) those forms of employment will not be undercut via AGI. Sorry to say, that misses the bigger picture, namely that AGI when combined with humanoid robots is coming not only for white-collar jobs but also blue-collar jobs too. It is a proverbial double-whammy when it comes to the attainment of AGI. Let’s talk about it. This analysis of an innovative AI breakthrough is part of my ongoing Forbes column coverage on the latest in AI, including identifying and explaining various impactful AI complexities (see the link here). Heading Toward AGI And ASI First, some fundamentals are required to set the stage for this weighty discussion. There is a great deal of research going on to further advance AI. The general goal is to either reach artificial general intelligence (AGI) or maybe even the outstretched possibility of achieving artificial superintelligence (ASI). AGI is AI that is considered on par with human intellect and can seemingly match our intelligence. ASI is AI that has gone beyond human intellect and would be superior in many if not all feasible ways. The idea is that ASI would be able to run circles around humans by outthinking us at every turn. For more details on the nature of conventional AI versus AGI and ASI, see my analysis at the link here. We have not yet attained AGI. In fact, it is unknown as to whether we will reach AGI, or that maybe AGI will be achievable in decades or perhaps centuries from now. The AGI attainment dates that are floating around are wildly varying and wildly unsubstantiated by any credible evidence or ironclad logic. ASI is even more beyond the pale when it comes to where we are currently with conventional AI. AGI Problem Only Half Seen Before launching into the primary matter at hand in this discussion, let’s contemplate a famous quote attributed to Charles Kettering, a legendary inventor, who said, “A problem well-stated is a problem half-solved.” I bring this up because those loud clamors right now about the assumption that AGI will replace white-collar workers are only seeing half of the problem. The problem as they see it is that since AGI is intellectually on par with humans, and since white-collar workers mainly use intellect in their work endeavors, AGI is going to be used in place of humans for white-collar work. I will in a moment explain why that’s only half of the problem and there is a demonstrative need to more carefully and fully articulate the nature of the problem. Will AGI Axiomatically Take White-Collar Jobs On a related facet, the belief that AGI will axiomatically replace white-collar labor makes a number of other related key assumptions. I shall briefly explore those and then come back to why the problem itself is only half-baked. The cost of using AGI for doing white-collar work will need to be presumably a better ROI choice over human workers. If not, then an employer would be wiser to stick with humans rather than employing AGI. There seems to often be an unstated belief that AGI is necessarily going to be a less costly route than employing humans. We don’t know yet what the cost of using AGI will be. It could be highly expensive. Indeed, some are worried that the world will divide into the AGI haves and AGI have-nots, partially due to the exorbitant cost that AGI might involve. If AGI is free to use, well, that would seem to be the nail in the coffin related to using human workers for the same capacity. Another angle is that AGI is relatively inexpensive in comparison to human labor. In that case, the use of AGI is likely to win over human labor usage. But if the cost of AGI is nearer to the cost of human labor (all in), or more so, then employers would rationally need to weigh the use of one versus the other. Note that when referring to the cost of human labor, there is more to that calculation than simply the dollar-hour labor rate per se. There are lots of other less apparent costs, such as the cost to manage human labor, the cost of dealing with HR-related issues, and many other factors that come into the weighty matter. Thus, an AGI versus human labor ROI will be more complex than it might seem at an initial glance. In addition, keep in mind that AGI would seemingly be readily switched on and off, and have other capacities that human labor would not equally tend to allow. The Other Half Is Coming Too Assume that by and large the advent of AGI will decimate the need for white-collar human labor. The refrain right now is that people should begin tilting toward blue-collar jobs as an alternative to white-collar jobs. This is a logical form of thinking in the sense that AGI as an intellectual mechanism would be unable to compete in jobs that involve hands-on work. A plumber needs to come to your house and do hands-on work to fix your plumbing. This is a physicality that entails arriving at your physical home, physically bringing and using tools, and physically repairing your faulty home plumbing. A truck driver likewise needs to sit in the cab of a truck and drive the vehicle. These are physically based tasks. There is no getting around the fact that these are hands-on activities. Aha, yes, those are physical tasks, but that doesn’t necessarily mean that only human hands can perform them. The gradual emergence of humanoid robots will provide an alternative to human hands. A humanoid robot is a type of robot that is built to resemble a human in form and function. You’ve undoubtedly seen those types of robots in the many online video recordings showing them walking, jumping, grasping at objects, and so on. A tremendous amount of active research and development is taking place to devise humanoid robots. They look comical right now. You watch those videos and laugh when the robot trips over a mere stick lying on the ground, something that a human would seldom trip over. You scoff when a robot tries to grasp a coffee cup and inadvertently spills most of the coffee. It all seems humorous and a silly pursuit. Keep in mind that we are all observing the development process while it is still taking place. At some point, those guffaws of the humanoid robots will lessen. Humanoid robots will be as smooth and graceful as humans. This will continue to be honed. Eventually, humanoid robots will be less prone to physical errors that humans make. In a sense, the physicality of a humanoid robot will be on par with humans, if not better, due to its mechanical properties. Do not discount the coming era of quite physically capable humanoid robots. AGI And Humanoid Robots Pair Up You might remember that in The Wonderful Wizard of Oz, the fictional character known as The Strawman lacked a brain. Without seeming to anthropomorphize humanoid robots, the current situation is that those robots typically use a form of AI that is below the sophistication level of modern generative AI. That’s fine for now due to the need to first ensure that the physical movements of the robots get refined. I have discussed that a said-to-be realm of Physical AI is going to be a huge breakthrough with incredible ramifications, see my analysis at the link here. The idea underlying Physical AI is that the AI of today is being uplifted by doing data training on the physical world. This also tends to include the use of World Models, consisting of broad constructions about how the physical world works, such as that we are bound to operate under conditions of gravity, and other physical laws of nature, see the link here. The bottom line here is that there will be a close pairing of robust AI with humanoid robots. Imagine what a humanoid robot can accomplish if it is paired with AGI. I’ll break the suspense and point out that AGI paired with humanoid robots means that those robots readily enter the blue-collar worker realm. Suppose your plumbing needs fixing. No worries, a humanoid robot that encompasses AGI will be sent to your home. The AGI is astute enough to carry on conversations with you, and the AGI also fully operates the robot to undertake the plumbing tasks. How did the AGI-paired humanoid robot get to your home? Easy-peasy, it drove a car or truck to get there. I’ve previously predicted that all the work on devising autonomous vehicles and self-driving cars will get shaken up once we have suitable humanoid robots devised. There won’t be a need for a vehicle to contain self-driving capabilities. A humanoid robot will simply sit in the driver’s seat and drive the vehicle. This is a much more open-ended solution than having to craft components that go into and onto a vehicle to enable self-driving. See my coverage at the link here. Timing Is Notable One of the reasons that many do not give much thought to the pairing of AGI with humanoid robots is that today’s humanoid robots seem extraordinarily rudimentary and incapable of performing physical dexterity tasks on par with human capabilities. Meanwhile, there is brazen talk that AGI is just around the corner. AGI is said to be within our grasp. Let’s give the timing considerations a bit of scrutiny. There are three primary timing angles: Option 1: AGI first, then humanoid robots. AGI is attained before humanoid robots are sufficiently devised. Option 2: Humanoid robots first, then AGI. Humanoid robots are physically fluently adept before AGI is attained. Option 3: AGI and humanoid robots arrive about at the same time. AGI is attained and at the same time, it turns out that humanoid robots are fluently adept too, mainly by coincidence and not due to any cross-mixing. A skeptic would insist that there is a fourth possibility, consisting of the possibility that we never achieve AGI and/or we fail to achieve sufficiently physically capable humanoid robots. I am going to reject that possibility. Perhaps I am overly optimistic, but it seems to me that we will eventually attain AGI, and we will eventually attain physically capable humanoid robots. I shall next respectively consider each of the three genuinely reasonable possibilities. Option 1: AGI First, Then Humanoid Robots What if we manage to attain AGI before we manage to achieve physically fluent humanoid robots? That’s just fine. We would indubitably put AGI to work as a partner with humans in figuring out how we can push along the budding humanoid robot development process. It seems nearly obvious that with AGI’s capable assistance, we would overcome any bottlenecks and soon enough arrive at top-notch physically adept humanoid robots. At that juncture, we would then toss AGI into the humanoid robots and have ourselves quite an amazing combination. Option 2: Humanoid Robots First, Then AGI Suppose that we devise very physically adept humanoid robots but have not yet arrived at AGI. Are we in a pickle? Nope. We could use conventional advanced AI inside those humanoid robots. The combination would certainly be good enough for a wide variety of tasks. The odds are that we would need to be cautious about where such robots are utilized. Nonetheless, we would have essentially walking, talking, and productive humanoid robots. If AGI never happens, oh well, we end up with pretty good humanoid robots. On the other hand, once we arrive at AGI, those humanoid robots will be stellar. It’s just a matter of time. Option 3: AGI And Humanoid Robots At The Same Time Let’s consider the potential of AGI and humanoid robots perchance being attained around the same time. Assume that this timing isn’t due to an outright cross-mixing with each other. They just so happen to advance on a similar timeline. I tend to believe that’s the most likely of the three scenarios. Here’s why. First, despite all the hubris about AGI being within earshot, perhaps in the next year or two, which is a popular pronouncement by many AI luminaries, I tend to side with recent surveys of AI developers that put the date around the year 2040 (see my coverage at the link here). Some AI luminaires sneakily play with the definition of AGI in hopes of making their predictions come true sooner, akin to moving the goalposts to easily score points. For my coverage on Sam Altman’s efforts of moving the cheese regarding AGI attainment, see the link here. Second, if you are willing to entertain the year 2040 as a potential date for achieving AGI, that’s about 15 years from now. In my estimation, the advancements being made in humanoid robots will readily progress such that by 2040 they will be very physically adept. Probably be sooner, but let’s go with the year 2040 for ease of contemplation. In my view, we will likely have humanoid robots doing well enough that they will be put into use prior to arriving at AGI. The pinnacle of robust humanoid robots and the attainment of AGI will roughly coincide with each other. Two peas in a pod.Impact Of Enormous Consequences In an upcoming column posting, I will examine the enormous consequences of having AGI paired with fully physically capable humanoid robots. As noted above, this will have a humongous impact on white-collar work and blue-collar work. There will be gargantuan economic impacts, societal impacts, cultural impacts, and so on. Some final thoughts for now. A single whammy is already being hotly debated. The debates currently tend to be preoccupied with the loss of white-collar jobs due to the attainment of AGI. A saving grace seems to be that at least blue-collar jobs are going to be around and thriving, even once AGI is attained. The world doesn’t seem overly gloomy if you can cling to the upbeat posture that blue-collar tasks remain intact. The double whammy is a lot more to take in. But the double whammy is the truth. The truth needs to be faced. If you are having doubts as a human about the future, just remember the famous words of Vince Lombardi: “Winners never quit, and quitters never win.” Humankind can handle the double whammy. Stay tuned for my upcoming coverage of what this entails.

프린시펄 파이낸셜 그룹(Principal Financial Group, PFG)은 지난 몇 년 동안 AI 활용이 급증하면서 이를 종합적으로 관리할 수 있는 AI 거버넌스 전략과 이를 실행할 도구가 절실해졌다. PFG의 부사장 겸 최고 데이터 및 분석 책임자인 라제시 아로라는 “현재 자연어 처리, 머신러닝, 생성형 AI 모델 등 100건 이상의 AI 사용례를 운영 중이며, 이를 통해 사기 탐지, 보험

CIOs and business leaders know they’re sitting on a goldmine of business data. And while traditional tools such as business intelligence platforms and statistical analysis software can effectively surface insights from the collated data resources, doing so quickly, in real-time and at scale remains an unsolved challenge.Enterprise AI, when deployed responsibly and at scale, can turn these bottlenecks into opportunities. Acting quickly on data, even ‘live’ (during a customer interaction, for example), is one of the technology’s abilities, as is scalability: AI can process large amounts of information from disparate sources almost as easily as it can summarize a one-page spreadsheet.But deploying an AI solution in the modern enterprise isn’t simple. It takes structure, trust and the right talent. Along with the practical implementation challenges, using AI brings its own challenges, such as data governance, the need to impose guardrails on AI responses and training data, and persistent staffing issues.We met with Rani Radhakrishnan, PwC Principal, Technology Managed Services – AI, Data Analytics and Insights, to talk candidly about what’s working — and what’s holding back CIOs in their AI journey. We spoke ahead of her speaking engagement at TechEx AI & Big Data Expo North America, June 4 and 5, at the Santa Clara Convention Center.Rani is especially attuned to some of the governance, data privacy and sovereignty issues that face enterprises, having spent many years in her career working with numerous clients in the health sector — an area where issues like privacy, data oversight and above all data accuracy are make-or-break aspects of technology deployments.“It’s not enough to just have a prompt engineer or a Python developer. … You still need the human in the loop to curate the right training data sets, review and address any bias in the outputs.” —Rani Radhakrishnan, PwCFrom support to strategy: shifting expectations for AIRani said that there’s a growing enthusiasm from PwC’s clients for AI-powered managed services that can provide both business insights in every sector, and for the technology to be used more proactively, in so-called agentic roles where agents can independently act on data and user input; where autonomous AI agents can take action based on interactions with humans, access to data resources and automation.For example, PwC’s agent OS is a modular AI platform that connects systems and scales intelligent agents into workflows, many times faster than traditional computing methods. It’s an example of how PwC responds to the demand for AI from its clients, many of whom see the potential of this new technology, but lack the in-house expertise and staff to act on their needs.Depending on the sector of the organization, the interest in AI can come from many different places in the business. Proactive monitoring of physical or digital systems; predictive maintenance in manufacturing or engineering; or cost efficiencies won by automation in complex, customer-facing environments, are just a few examples.But regardless of where AI can bring value, most companies don’t yet have in-house the range of skills and people necessary for effective AI deployment — or at least, deployments that achieve ROI and don’t come with significant risk.“It’s not enough to just have a prompt engineer or a Python developer,” Rani said. “You’ve got to put all of these together in a very structured manner, and you still need the human in the loop to curate the right training data sets, review and address any bias in the outputs.”Cleaning house: the data challenge behind AIRani says that effective AI implementations need a mix of technical skills — data engineering, data science, prompt engineering — in combination with an organization’s domain expertise. Internal domain expertise can define the right outcomes, and technical staff can cover the responsible AI practices, like data collation and governance, and confirm that AI systems work responsibly and within company guidelines.“In order to get the most value out of AI, an organization has to get the underlying data right,” she said. “I don’t know of a single company that says its data is in great shape … you’ve got to get it into the right structure and normalize it properly so you can query, analyze, and annotate it and identify emerging trends.”Part of the work enterprises have to put in for effective AI use is the observation for and correction of bias — in both output of AI systems and in the analysis of potential bias inherent in training and operational data.It’s important that as part of the underlying architecture of AI systems, teams apply stringent data sanitization, normalization, and data annotation processes. The latter requires “a lot of human effort,” Rani said, and the skilled personnel required are among the new breed of data professionals that are beginning to emerge.If data and personnel challenges can be overcome, then the feedback loop makes the possible outcomes from generative AI really valuable, Rani said. “Now you have an opportunity with AI prompts to go back and refine the answer that you get. And that’s what makes it so unique and so valuable because now you’re training the model to answer the questions the way you want them answered.”For CIOs, the shift isn’t just about tech enablement. It’s about integrating AI into enterprise architecture, aligning with business strategy, and managing the governance risks that come with scale. CIOs are becoming AI stewards — architecting not just systems, but trust and transformation.ConclusionIt’s only been a few years since AI emerged from its roots in academic computer science research, so it’s understandable that today’s enterprise organizations are, to a certain extent, feeling their way towards realizing AI’s potential.But a new playbook is emerging — one that helps CIOs access the value held in their data reserves, in business strategy, operational improvement, customer-facing experiences and a dozen more areas of the business.As a company that’s steeped in experience with clients large and small from all over the world, PwC is one of the leading choices that decision-makers turn to, to begin or rationalize and direct their existing AI journeys.Explore how PwC is helping CIOs embed AI into core operations, and see Rani’s latest insights at the June TechEx AI & Big Data Expo North America.(Image source: “Network Rack” by one individual is licensed under CC BY-SA 2.0.)

Drones Set To Deliver Benefits for Labor-Intensive Industries: Forrester By John P. Mello Jr. June 3, 2025 5:00 AM PT ADVERTISEMENT Quality Leads That Turn Into Deals Full-service marketing programs from TechNewsWorld deliver sales-ready leads. Segment by geography, industry, company size, job title, and more. Get Started Now. Aerial drones are rapidly assuming a key role in the physical automation of business operations, according to a new report by Forrester Research. Aerial drones power airborne physical automation by addressing operational challenges in labor-intensive industries, delivering efficiency, intelligence, and experience, explained the report written by Principal Analyst Charlie Dai with Frederic Giron, Merritt Maxim, Arjun Kalra, and Bill Nagel. Some industries, like the public sector, are already reaping benefits, it continued. The report predicted that drones will deliver benefits within the next two years as technologies and regulations mature. It noted that drones can help organizations grapple with operational challenges that exacerbate risks and inefficiencies, such as overreliance on outdated, manual processes, fragmented data collection, geographic barriers, and insufficient infrastructure. Overreliance on outdated manual processes worsens inefficiencies in resource allocation and amplifies safety risks in dangerous work environments, increasing operational costs and liability, the report maintained. “Drones can do things more safely, at least from the standpoint of human risk, than humans,” said Rob Enderle, president and principal analyst at the Enderle Group, an advisory services firm, in Bend, Ore. “They can enter dangerous, exposed, very high-risk and even toxic environments without putting their operators at risk,” he told TechNewsWorld. “They can be made very small to go into areas where people can’t physically go. And a single operator can operate several AI-driven drones operating autonomously, keeping staffing levels down.” Sensor Magic “The magic of the drone is really in the sensor, while the drone itself is just the vehicle that holds the sensor wherever it needs to be,” explained DaCoda Bartels, senior vice president of operations with FlyGuys, a drone services provider, in Lafayette, La. “In doing so, it removes all human risk exposure because the pilot is somewhere safe on the ground, sending this sensor, which is, in most cases, more high-resolution than even a human eye,” he told TechNewsWorld. “In essence, it’s a better data collection tool than if you used 100 people. Instead, you deploy one drone around in all these different areas, which is safer, faster, and higher resolution.” Akash Kadam, a mechanical engineer with Caterpillar, maker of construction and mining equipment, based in Decatur, Ill., explained that drones have evolved into highly functional tools that directly respond to key inefficiencies and threats to labor-intensive industries. “Within the manufacturing and supply chains, drones are central to optimizing resource allocation and reducing the exposure of humans to high-risk duties,” he told TechNewsWorld. “Drones can be used in factory environments to automatically inspect overhead cranes, rooftops, and tight spaces — spaces previously requiring scaffolding or shutdowns, which carry both safety and cost risks,” he said. “A reduction in downtime, along with no requirement for manual intervention in hazardous areas, is provided through this aerial inspection by drones.” “In terms of resource usage, drones mounted with thermal cameras and tools for acquiring real-time data can spot bottlenecks, equipment failure, or energy leakage on the production floor,” he continued. “This can facilitate predictive maintenance processes and [optimal] usage of energy, which are an integral part of lean manufacturing principles.” Kadam added that drones provide accurate field mapping and multispectral imaging in agriculture, enabling the monitoring of crop health, soil quality, and irrigation distribution. “Besides the reduction in manual scouting, it ensures more effective input management, which leads to more yield while saving resources,” he observed. Better Data Collection The Forrester report also noted that drones can address problems with fragmented data collection and outdated monitoring systems. “Drones use cameras and sensors to get clear, up-to-date info,” said Daniel Kagan, quality manager at Rogers-O’Brien Construction, a general contractor in Dallas. “Some drones even make 3D maps or heat maps,” he told TechNewsWorld. “This helps farmers see where crops need more water, stores check roof damage after a storm, and builders track progress and find delays.” “The drone collects all this data in one flight, and it’s ready to view in minutes and not days,” he added. Dean Bezlov, global head of business development at MYX Robotics, a visualization technology company headquartered in Sofia, Bulgaria, added that drones are the most cost and time-efficient way to collect large amounts of visual data. “We are talking about two to three images per second with precision and speed unmatched by human-held cameras,” he told TechNewsWorld. “As such, drones are an excellent tool for ‘digital twins’ — timestamps of the real world with high accuracy which is useful in industries with physical assets such as roads, rail, oil and gas, telecom, renewables and agriculture, where the drone provides a far superior way of looking at the assets as a whole,” he said. Drone Adoption Faces Regulatory Hurdles While drones have great potential for many organizations, they will need to overcome some challenges and barriers. For example, Forrester pointed out that insurers deploy drones to evaluate asset risks but face evolving privacy regulations and gaps in data standardization. Media firms use drones to take cost-effective, cinematic aerial footage, but face strict regulations, it added, while in urban use cases like drone taxis and cargo transport remain experimental due to certification delays and airspace management complexities. “Regulatory frameworks, particularly in the U.S., remain complex, bureaucratic, and fragmented,” said Mark N. Vena, president and principal analyst with SmartTech Research in Las Vegas. “The FAA’s rules around drone operations — especially for flying beyond visual line of sight [BVLOS] — are evolving but still limit many high-value use cases.” “Privacy concerns also persist, especially in urban areas and sectors handling sensitive data,” he told TechNewsWorld. “For almost 20 years, we’ve been able to fly drones from a shipping container in one country, in a whole other country, halfway across the world,” said FlyGuys’ Bartels. “What’s limiting the technology from being adopted on a large scale is regulatory hurdles over everything.” Enderle added that innovation could also be a hangup for organizations. “This technology is advancing very quickly, making buying something that isn’t instantly obsolete very difficult,” he said. “In addition, there are a lot of drone choices, raising the risk you’ll pick one that isn’t ideal for your use case.” “We are still at the beginning of this trend,” he noted. “Robotic autonomous drones are starting to come to market, which will reduce dramatically the need for drone pilots. I expect that within 10 years, we’ll have drones doing many, if not most, of the dangerous jobs currently being done by humans, as robotics, in general, will displace much of the labor force.” John P. Mello Jr. has been an ECT News Network reporter since 2003. His areas of focus include cybersecurity, IT issues, privacy, e-commerce, social media, artificial intelligence, big data and consumer electronics. He has written and edited for numerous publications, including the Boston Business Journal, the Boston Phoenix, Megapixel.Net and Government Security News. Email John. Leave a Comment Click here to cancel reply. Please sign in to post or reply to a comment. New users create a free account. Related Stories More by John P. Mello Jr. view all More in Emerging Tech

It’s easy to look at President Donald Trump’s second term and conclude that the less power and reach the federal government has, the better. After all, a smaller government might provide Trump or someone like him with fewer opportunities to disrupt people’s lives, leaving America less vulnerable to the whims of an aspiring autocrat. Weaker law-enforcement agencies could lack the capacity to enforce draconian policies. The president would have less say in how universities like Columbia conduct their business if they weren’t so dependent on federal funding. And he would have fewer resources to fundamentally change the American way of life.Trump’s presidency has the potential to reshape an age-old debate between the left and the right: Is it better to have a big government or a small one? The left, which has long advocated for bigger government as a solution to society’s problems, might be inclined to think that in the age of Trump, a strong government may be too risky. Say the United States had a single-payer universal health care system, for example. As my colleague Kelsey Piper pointed out, the government would have a lot of power to decide what sorts of medical treatments should and shouldn’t be covered, and certain forms of care that the right doesn’t support — like abortion or transgender health — would likely get cut when they’re in power. That’s certainly a valid concern. But the dangers Trump poses do not ultimately make the case for a small or weak government because the principal problem with the Trump presidency is not that he or the federal government has too much power. It’s that there’s not enough oversight.Reducing the power of the government wouldn’t necessarily protect us. In fact, “making government smaller” is one of the ways that Trump might be consolidating power.First things first: What is “big government”?When Americans are polled about how they feel about “big government” programs — policies like universal health care, Social Security, welfare for the poor — the majority of people tend to support them. Nearly two-thirds of Americans believe the government should be responsible for ensuring everyone has health coverage. But when you ask Americans whether they support “big government” in the abstract, a solid majority say they view it as a threat.That might sound like a story of contradictions. But it also makes sense because “big government” can have many different meanings. It can be a police state that surveils its citizens, an expansive regulatory state that establishes and enforces rules for the private sector, a social welfare state that directly provides a decent standard of living for everyone, or some combination of the three. In the United States, the debate over “big government” can also include arguments about federalism, or how much power the federal government should have over states. All these distinctions complicate the debate over the size of government: Because while someone might support a robust welfare system, they might simultaneously be opposed to being governed by a surveillance state or having the federal government involved in state and local affairs.As much as Americans like to fantasize about small government, the reality is that the wealthiest economies in the world have all been a product of big government, and the United States is no exception. That form of government includes providing a baseline social safety net, funding basic services, and regulating commerce. It also includes a government that has the capacity to enforce its rules and regulations.A robust state that caters to the needs of its people, that is able to respond quickly in times of crisis, is essential. Take the Covid-19 pandemic. The US government, under both the Trump and Biden administrations, was able to inject trillions of dollars into the economy to avert a sustained economic downturn. As a result, people were able to withstand the economic shocks, and poverty actually declined. Stripping the state of the basic powers it needs to improve the lives of its citizens will only make it less effective and erode people’s faith in it as a central institution, making people less likely to participate in the democratic process, comply with government policies, or even accept election outcomes.A constrained government does not mean a small governmentBut what happens when the people in power have no respect for democracy? The argument for a weaker and smaller government often suggests that a smaller government would be more constrained in the harm it can cause, while big government is more unrestrained. In this case, the argument is that if the US had a smaller government, then Trump could not effectively use the power of the state — by, say, deploying federal law enforcement agencies or withholding federal funds — to deport thousands of immigrants, bully universities, and assault fundamental rights like the freedom of speech. But advocating for bigger government does not mean you believe in handing the state unlimited power to do as it pleases. Ultimately, the most important way to constrain government has less to do with its size and scope and more to do with its checks and balances. In fact, one of the biggest checks on Trump’s power so far has been the structure of the US government, not its size. Trump’s most dangerous examples of overreach — his attempts to conduct mass deportations, eliminate birthright citizenship, and revoke student visas and green cards based on political views — have been an example of how proper oversight has the potential to limit government overreach. To be sure, Trump’s policies have already upended people’s lives, chilled speech, and undermined the principle of due process. But while Trump has pushed through some of his agenda, he hasn’t been able to deliver at the scale he promised. But that’s not because the federal government lacks the capacity to do those things. It’s because we have three equal branches of government, and the judicial branch, for all of its shortcomings in the Trump era, is still doing its most basic job to keep the executive branch in check. Reforms should include more oversight, not shrinking governmentThe biggest lesson from Trump’s first term was that America’s system of checks and balances — rules and regulations, norms, and the separate branches of government — wasn’t strong enough. As it turned out, a lot of potential oversight mechanisms did not have enough teeth to meaningfully restrain the president from abusing his power. Trump incited an assault on the US Capitol in an effort to overturn the 2020 election, and Congress ultimately failed in its duty to convict him for his actions. Twice, impeachment was shown to be a useless tool to keep a president in check.But again that’s a problem of oversight, not of the size and power of government. Still, oversight mechanisms need to be baked into big government programs to insulate them from petty politics or volatile changes from one administration to the next. Take the example of the hypothetical single-payer universal health care system. Laws dictating which treatments should be covered should be designed to ensure that changes to them aren’t dictated by the president alone, but through some degree of consensus that involves regulatory boards, Congress, and the courts. Ultimately, social programs should have mechanisms that allow for change so that laws don’t become outdated, as they do now. And while it’s impossible to guarantee that those changes will always be good, the current system of employer-sponsored health insurance is hardly a stable alternative.By contrast, shrinking government in the way that Republicans often talk about only makes people more vulnerable. Bigger governments — and more bureaucracy — can also insulate public institutions from the whims of an erratic president. For instance, Trump has tried to shutter the Consumer Financial Protection Bureau (CFPB), a regulatory agency that gets in the way of his and his allies’ business. This assault allows Trump to serve his own interests by pleasing his donors.In other words, Trump is currently trying to make government smaller — by shrinking or eliminating agencies that get in his way — to consolidate power. “Despite Donald Trump’s rhetoric about the size or inefficiency of government, what he has done is eradicate agencies that directly served people,” said Julie Margetta Morgan, president of the Century Foundation who served as an associate director at the CFPB. “He may use the language of ‘government inefficiency’ to accomplish his goals, but I think what we’re seeing is that the goals are in fact to open up more lanes for big businesses to run roughshod over the American people.” The problem for small-government advocates is that the alternative to big government is not just small government. It’s also big business because fewer services, rules, and regulations open up the door to privatization and monopolization. And while the government, however big, has to answer to the public, businesses are far less accountable. One example of how business can replace government programs is the Republicans’ effort to overhaul student loan programs in the latest reconciliation bill the House passed, which includes eliminating subsidized loans and limiting the amount of aid students receive. The idea is that if students can’t get enough federal loans to cover the cost of school, they’ll turn to private lenders instead. “It’s not only cutting Pell Grants and the affordability of student loan programs in order to fund tax cuts to the wealthy, but it’s also creating a gap where [private lenders] are all too happy to come in,” Margetta Morgan said. “This is the small government alternative: It’s cutting back on programs that provided direct services for people — that made their lives better and more affordable — and replacing it with companies that will use that gap as an opportunity for extraction and, in some cases, for predatory services.”Even with flawed oversight, a bigger and more powerful government is still preferable because it can address people’s most basic needs, whereas small government and the privatization of public services often lead to worse outcomes.So while small government might sound like a nice alternative when would-be tyrants rise to power, the alternative to big government would only be more corrosive to democracy, consolidating power in the hands of even fewer people (and businesses). And ultimately, there’s one big way for Trump to succeed at destroying democracy, and that’s not by expanding government but by eliminating the parts of government that get in his way.See More:

Limited-time offer: Get more than 30% off a Vox Membership. Join today to support independent journalism. Federal civil servants are supposed to enjoy robust protections against being fired or demoted for political reasons. But President Donald Trump has effectively stripped them of these protections by neutralizing the federal agencies that implement these safeguards.An agency known as the Merit Systems Protection Board (MSPB) hears civil servants’ claims that a “government employer discriminated against them, retaliated against them for whistleblowing, violated protections for veterans, or otherwise subjected them to an unlawful adverse employment action or prohibited personnel practice,” as a federal appeals court explained in an opinion on Tuesday. But the three-member board currently lacks the quorum it needs to operate because Trump fired two of the members.Trump also fired Hampton Dellinger, who until recently served as the special counsel of the United States, a role that investigates alleged violations of federal civil service protections and brings related cases to the MSPB. Trump recently nominated Paul Ingrassia, a far-right podcaster and recent law school graduate to replace Dellinger.The upshot of these firings is that no one in the government is able to enforce laws and regulations protecting civil servants. As Dellinger noted in an interview, the morning before a federal appeals court determined that Trump could fire him, he’d “been able to get 6,000 newly hired federal employees back on the job,” and was working to get “all probationary employees put back on the job [after] their unlawful firing” by the Department of Government Efficiency and other Trump administration efforts to cull the federal workforce. These and other efforts to reinstate illegally fired federal workers are on hold, and may not resume until Trump leaves office.Which brings us to the US Court of Appeals for the Fourth Circuit’s decision in National Association of Immigration Judges v. Owen, which proposes an innovative solution to this problem.As the Owen opinion notes, the Supreme Court has held that the MSPB process is the only process a federal worker can use if they believe they’ve been fired in violation of federal civil service laws. So if that process is shut down, the worker is out of luck.But the Fourth Circuit’s Owen opinion argues that this “conclusion can only be true…when the statute functions as Congress intended.” That is, if the MSPB and the special counsel are unable to “fulfill their roles prescribed by” federal law, then the courts should pick up the slack and start hearing cases brought by illegally fired civil servants.For procedural reasons, the Fourth Circuit’s decision will not take effect right away — the court sent the case back down to a trial judge to “conduct a factual inquiry” into whether the MSPB continues to function. And, even after that inquiry is complete, the Trump administration is likely to appeal the Fourth Circuit’s decision to the Supreme Court if it wants to keep civil service protections on ice.If the justices agree with the circuit court, however, that will close a legal loophole that has left federal civil servants unprotected by laws that are still very much on the books. And it will cure a problem that the Supreme Court bears much of the blame for creating.The “unitary executive,” or why the Supreme Court is to blame for the loss of civil service protectionsFederal law provides that Dellinger could “be removed by the President only for inefficiency, neglect of duty, or malfeasance in office,” and members of the MSPB enjoy similar protections against being fired. Trump’s decision to fire these officials was illegal under these laws.But a federal appeals court nonetheless permitted Trump to fire Dellinger, and the Supreme Court recently backed Trump’s decision to fire the MSPB members as well. The reason is a legal theory known as the “unitary executive,” which is popular among Republican legal scholars, and especially among the six Republicans that control the Supreme Court.If you want to know all the details of this theory, I can point you to three different explainers I’ve written on the unitary executive. The short explanation is that the unitary executive theory claims that the president must have the power to fire top political appointees charged with executing federal laws – including officials who execute laws protecting civil servants from illegal firings.But the Supreme Court has never claimed that the unitary executive permits the president to fire any federal worker regardless of whether Congress has protected them or not. In a seminal opinion laying out the unitary executive theory, for example, Justice Antonin Scalia argued that the president must have the power to remove “principal officers” — high-ranking officials like Dellinger who must be nominated by the president and confirmed by the Senate. Under Scalia’s approach, lower-ranking government workers may still be given some protection.The Fourth Circuit cannot override the Supreme Court’s decision to embrace the unitary executive theory. But the Owen opinion essentially tries to police the line drawn by Scalia. The Supreme Court has given Trump the power to fire some high-ranking officials, but he shouldn’t be able to use that power as a back door to eliminate job protections for all civil servants.The Fourth Circuit suggests that the federal law which simultaneously gave the MSPB exclusive authority over civil service disputes, while also protecting MSPB members from being fired for political reasons, must be read as a package. Congress, this argument goes, would not have agreed to shunt all civil service disputes to the MSPB if it had known that the Supreme Court would strip the MSPB of its independence. And so, if the MSPB loses its independence, it must also lose its exclusive authority over civil service disputes — and federal courts must regain the power to hear those cases.It remains to be seen whether this argument persuades a Republican Supreme Court — all three of the Fourth Circuit judges who decided the Owen case are Democrats, and two are Biden appointees. But the Fourth Circuit’s reasoning closely resembles the kind of inquiry that courts frequently engage in when a federal law is struck down.When a court declares a provision of federal law unconstitutional, it often needs to ask whether other parts of the law should fall along with the unconstitutional provision, an inquiry known as “severability.” Often, this severability analysis asks which hypothetical law Congress would have enacted if it had known that the one provision is invalid.The Fourth Circuit’s decision in Owen is essentially a severability opinion. It takes as a given the Supreme Court’s conclusion that laws protecting Dellinger and the MSPB members from being fired are unconstitutional, then asks which law Congress would have enacted if it had known that it could not protect MSPB members from political reprisal. The Fourth Circuit’s conclusion is that, if Congress had known that MSPB members cannot be politically independent, then it would not have given them exclusive authority over civil service disputes.If the Supreme Court permits Trump to neutralize the MSPB, that would fundamentally change how the government functionsThe idea that civil servants should be hired based on merit and insulated from political pressure is hardly new. The first law protecting civil servants, the Pendleton Civil Service Reform Act, which President Chester A. Arthur signed into law in 1883.Laws like the Pendleton Act do more than protect civil servants who, say, resist pressure to deny government services to the president’s enemies. They also make it possible for top government officials to actually do their jobs.Before the Pendleton Act, federal jobs were typically awarded as patronage — so when a Democratic administration took office, the Republicans who occupied most federal jobs would be fired and replaced by Democrats. This was obviously quite disruptive, and it made it difficult for the government to hire highly specialized workers. Why would someone go to the trouble of earning an economics degree and becoming an expert on federal monetary policy, if they knew that their job in the Treasury Department would disappear the minute their party lost an election?Meanwhile, the task of filling all of these patronage jobs overwhelmed new presidents. As Candice Millard wrote in a 2011 biography of President James A. Garfield, the last president elected before the Pendleton Act, when Garfield took office, a line of job seekers began to form outside the White House “before he even sat down to breakfast.” By the time Garfield had eaten, this line “snaked down the front walk, out the gate, and onto Pennsylvania Avenue.” Garfield was assassinated by a disgruntled job seeker, a fact that likely helped build political support for the Pendleton Act.By neutralizing the MSPB, Trump is effectively undoing nearly 150 years worth of civil service reforms, and returning the federal government to a much more primitive state. At the very least, the Fourth Circuit’s decision in Owen is likely to force the Supreme Court to ask if it really wants a century and a half of work to unravel.See More:

John Edwards, Technology Journalist & AuthorJune 4, 20254 Min ReadRancz Andrei via Alamy Stock PhotoIt may be hard to believe, but some senior executives actually believe that AI's arrival isn't a ground-shaking event. These individuals tend to be convinced that while AI may be a useful tool in certain situations, it's not going to change business in any truly meaningful way. Call them skeptics or call them realists, but such individuals really do exist, and it's the enterprise's CIOs and other IT leaders who need to gently guide them into reality. AI adoption tends to fall into three mindsets: early adopters who recognize its benefits, skeptics who fear its risks, and a large middle group -- those who are curious, but uncertain, observes Dave McQuarrie, HP's chief commercial officer in an online interview. "The key to closing the AI adoption gap lies in engaging this middle group, equipping them with knowledge, and guiding them through practical implementation." Effective Approaches The most important move is simply getting started. Establish a group of advocates in your company to serve as your early AI adopters, McQuarrie says. "Pick two or three processes to completely automate rather than casting a wide net, and use these as case studies to learn from," he advises. "By beginning with a subset of users, leaders can develop a solid foundation as they roll out the tool more widely across their business." Related:Start small, gather data, and present your use case, demonstrating how AI can support you and your colleagues to do your jobs better and faster, recommends Nicola Cain, CEO and principal consultant at Handley Gill Limited, a UK-based legal, regulatory and compliance consultancy. "This could be by analyzing customer interactions to demonstrate how the introduction of a chatbot to give customers prompt answers to easily addressed questions ... or showing how vast volumes of network log data could be analyzed by AI to identify potentially malign incidents that warrant further investigation," she says in an email interview. Changing Mindsets Question the skeptical leader about their biggest business bottleneck, suggests Jeff Mains, CEO of business consulting firm Champion Leadership Group. "Whether it’s slow decision-making, inconsistent customer experiences, or operational inefficiencies, there's a strategic AI-driven solution for nearly every major business challenge," he explains in an online interview. "The key is showing leaders how AI directly solves their most pressing problems today." When dealing with a reluctant executive, start by identifying an AI use case, Cain says. "AI functionality already performs strongly in areas like forecasting, recognition, event detection, personalization, interaction support, recommendations, and goal-driven optimization," she states. "Good business areas to identify a potential use case could therefore be in finance, customer service, marketing, cyber security, or stock control." Related:Strengthening Your Case Executives respond to proof, not promises, Mains says. "Instead of leading with research reports, I’ve found that real, industry-specific case studies are far more impactful," he observes. "If a direct competitor has successfully integrated AI into sales, marketing, or operations, use that example, because it creates urgency." Instead of just citing AI-driven efficiency gains, Mains recommends framing AI as a way to free-up leadership to focus on high-level strategy rather than day-to-day operations. Instead of trying to pitch AI in broad terms, Mains advises aligning the technology to the company's stated goals. "If the company is struggling with customer retention, talk about how AI can improve personalization," he suggests. "If operational inefficiencies are a problem, highlight AI-driven automation." The moment AI is framed as a business enabler rather than a technology trend, the conversation shifts from resistance to curiosity. Related:When All Else Fails If leadership refuses to embrace AI, it’s important to document the cost of inaction, Mains says. "Keep track of inefficiencies, missed opportunities, and competitor advancements," he recommends. Sometimes, leadership only shifts when management’s view of the risks of staying stagnant outweigh the risks of change. "If a company refuses to innovate despite clear benefits, that’s a red flag for long-term growth." Final Thoughts For enterprises that have so far done little or nothing in the way of AI deployment, the technology may appear optional, McQuarrie observes. Yet soon, operating without AI will become as unthinkable as running a business without the internet. Enterprise leaders who delay AI adoption risk falling behind the competition. "The best approach is to embrace a mindset of humility and curiosity -- actively seek out knowledge, ask questions, and learn from peers who are already seeing AI’s impact," he says. "To stay competitive in this rapidly evolving landscape, leaders should start now." The best companies aren't just using AI to improve; they're using the technology to redefine how they do business, Mains says. Leaders who recognize AI as a business accelerator will be the ones leading their industries in the next decade. "Those who hesitate? They’ll be playing catch-up." he concludes. About the AuthorJohn EdwardsTechnology Journalist & AuthorJohn Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.See more from John EdwardsWebinarsMore WebinarsReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like

Ookwemin Minising Aerial photo with project area outline. Credit: Waterfront Toronto Global professional services company, GHD, and Danish nature-based design studio, SLA, have been awarded the role of prime consultant by Waterfront Toronto for phase one of infrastructure and streetscape design for a new island community. Formerly known as Villiers Island, Ookwemin Minising is a new island born from an ambitious flood protection and river restoration project. The Don River, a historic gathering place, will be at the heart of this future community. The island, which is planned to be home to more than 15,000 people, will also be a destination where people will visit to relax and explore. The first new residents of this island community are expected to move in by 2031. For the project, GHD, the prime consultant and technical lead, and SLA, design lead for urban realm and landscape, will deliver a new urban environment that aims to honour the legacy of the Don River through an approach rooted in resilient infrastructure, cultural memory and deep ecological integration. Drawing inspiration from global precedents and local Indigenous knowledge, the team’s “Growing Streets” concept proposes streetscapes that evolve like living ecosystems. “This project represents a significant milestone for Toronto’s waterfront revitalization,” said Chris Hunter, GHD chief executive officer for the Americas. “By integrating innovative engineering with responsive design, our team will help create infrastructure that’s not just functional, but truly adaptive to community needs while honoring the ecological transformation nearing completion at the Don River mouth. This approach exemplifies our commitment to building resilient systems that evolve with the communities they serve.” The team, which includes architects Allies and Morrison, will integrate design for streetscapes and public realm with a review of the density and built form on the island, building on years of planning to realize this new neighbourhood. “Tri-government investment unlocked the potential of the Port Lands, allowing us to create a brand new island,” says Chris Glaisek, chief planning and design officer at Waterfront Toronto. “Now, renewed investment in waterfront revitalization means this new island is ready to launch. By integrating design for streets and public realm with a review of built form on the island, this team can build on the planning done by the City of Toronto, Waterfront Toronto and CreateTO to deliver as much new housing as possible, while building a truly world-class neighbourhood.” At the heart of the team’s vision for Ookwemin Minising lies a next-practice model for climate-adaptive urbanism. Guided by seven core principles, including surface-level rainwater management, soil repurposing, native vegetation and social spaces that foster mobility and interaction, the design will champion active mobility through integrated pedestrian and biodiversity corridors woven throughout the island. These corridors can provide optimal microclimates for outdoor comfort while managing storm water, linking and strengthening ecologies and connecting people with nature. Informed by leading examples from cities like Copenhagen, Oslo, and London, the design will seek to maximize sustainability without relying on future technologies. “We’re thrilled to bring our Growing Streets vision to life in Toronto,” said Rasmus Astrup, design principal and partner at SLA. “This is urban design at its most alive – where trees, water, wind, soil and people grow and flow together. The streetscape design of Ookwemin Minising is not just about infrastructure, it’s about creating a living cityscape that breathes with the seasons, nurtures biodiversity and supports everyday life in inspiring, joyful ways. In Ookwemin Minising, every street becomes a celebration – of the land, of the water, of our heritage and of all the life of Toronto.” The infrastructure designs for Ookwemin Minising will incorporate  plantings, nature-integrated public seating, and climate-buffering vegetation to create a vibrant and adaptive civic experience. The team envisions a design that would build public awareness of ecological processes while enhancing urban resilience and well-being. The vision embraces a holistic design approach that integrates street configurations, building scales, and public spaces to create a cohesive and sustainable community. Rooted in the values of the surrounding Port Lands and celebrating the area’s enduring industrial, maritime and Indigenous histories, the team’s design for Ookwemin Minising will aim to set a new benchmark for culturally and ecologically responsive waterfront development in North America. The project will be brought to life by a group of industry-leading consultants, including:  GHD (prime consultant): Engineering design services, planning services, environmental services and construction administration SLA: Design lead for urban realm and landscape Trophic Design: Co-designer with SLA for Indigenous landscape design and knowledge Transsolar: Sustainability and low-carbon infrastructure systems Monumental Projects: Public engagement and community outreach Level Playing Field: Accessibility services Allies and Morrison: Architectural lead   The post GHD and SLA teaming up to deliver major infrastructure design for Toronto’s newest island appeared first on Canadian Architect.

html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN" "http://www.w3.org/TR/REC-html40/loose.dtd" New York-based architecture practice HWKN Architecture has released plans for the first ground up AI-driven office community in the United Arab Emirates.Called District 11, the new development is envisioned as the world's first office community built from the ground up that is positioned, created, and programmed by artificial intelligence (AI) at a time when society is at a turning point in architecture and technology is changing the design process. The world's first office community created by AIHWKN was chosen by Al Marwan Real Estate Development Group to create District 11, a ground-breaking, AI-powered work and lifestyle complex that aims to transform community and productivity in the United Arab Emirates. As District 11, guided by HWKN's Founding Principal, Matthias Hollwich, is constructed for the future of business and well-being, this creative project, which spans eleven different buildings, effortlessly combines work, leisure, and culture with HWKN's state-of-the-art design, the development's smart services, and flexible spaces. In order to create the AI prompts for the eleven buildings in District 11, HWKN did a great deal of study and immersed themselves in Sharjah's environment, history, and culture. Since there has never been a commercial neighborhood like District 11 in Sharjah, HWKN's hyper-contextual process takes into consideration the community's intense heat and the requirement for productive workspaces. The end product is a forward-thinking work resort that is a walking neighborhood with smart offices, nurseries, medical facilities, and a mosque, as well as distinctively constructed buildings that strategically create shade for the public areas.After launching the Work Resort concept at Canada Water Dockside, HWKN is now creating the first workplace community designed in partnership with AI by leveraging the technology to improve architectural designs and quality of life. For both current and potential renters, HWKN's AI-driven procedure maximizes the worker experience to promote human connection, shared experiences, and physical expression. A simplified route from concept to reality that welcomes innovative ideas, adapts to all environmental conditions, and effectively realizes ambitious ambitions is made possible by a special reverse-engineering method. In order to introduce this new kind of business environment into what was formerly a city that was exclusively residential, HWKN is using AI to create structures that blend in perfectly with Sharjah's identity as an Arab cultural capital and center for the arts, home to renowned museums like the Sharjah Museum of Islamic Civilization and the Sharjah Art Museum, as well as hosting the Sharjah Biennial.By embracing new ideas and creating communities that will change with the design business, Matthias is setting the path for the future generation of architects. Matthias, who formerly worked with Rem Koolhas at Eisenman Architects and OMA, provides more than ten years of expertise with creative approaches to the future of architecture and strategic thinking.HWKN also completed the third tower of the iconic Journal Squared Project in New Jersey, realizing a ten-year vision for urban transformation. Based in NYC, HWKN is a global architectural innovation company. The firm, established in 2008, is headed by Matthias Hollwich and partners Jessica Knobloch, Dorin Baul, Robert May, and Olga Snowden. It has collaborating offices in Munich, Miami, Berlin, Riyadh, and London.All renderings courtesy of HWKN.> via HWKN

John Edwards, Technology Journalist & AuthorJune 4, 20254 Min ReadRancz Andrei via Alamy Stock PhotoIt may be hard to believe, but some senior executives actually believe that AI's arrival isn't a ground-shaking event. These individuals tend to be convinced that while AI may be a useful tool in certain situations, it's not going to change business in any truly meaningful way. Call them skeptics or call them realists, but such individuals really do exist, and it's the enterprise's CIOs and other IT leaders who need to gently guide them into reality. AI adoption tends to fall into three mindsets: early adopters who recognize its benefits, skeptics who fear its risks, and a large middle group -- those who are curious, but uncertain, observes Dave McQuarrie, HP's chief commercial officer in an online interview. "The key to closing the AI adoption gap lies in engaging this middle group, equipping them with knowledge, and guiding them through practical implementation." Effective Approaches The most important move is simply getting started. Establish a group of advocates in your company to serve as your early AI adopters, McQuarrie says. "Pick two or three processes to completely automate rather than casting a wide net, and use these as case studies to learn from," he advises. "By beginning with a subset of users, leaders can develop a solid foundation as they roll out the tool more widely across their business." Related:Start small, gather data, and present your use case, demonstrating how AI can support you and your colleagues to do your jobs better and faster, recommends Nicola Cain, CEO and principal consultant at Handley Gill Limited, a UK-based legal, regulatory and compliance consultancy. "This could be by analyzing customer interactions to demonstrate how the introduction of a chatbot to give customers prompt answers to easily addressed questions ... or showing how vast volumes of network log data could be analyzed by AI to identify potentially malign incidents that warrant further investigation," she says in an email interview. Changing Mindsets Question the skeptical leader about their biggest business bottleneck, suggests Jeff Mains, CEO of business consulting firm Champion Leadership Group. "Whether it’s slow decision-making, inconsistent customer experiences, or operational inefficiencies, there's a strategic AI-driven solution for nearly every major business challenge," he explains in an online interview. "The key is showing leaders how AI directly solves their most pressing problems today." When dealing with a reluctant executive, start by identifying an AI use case, Cain says. "AI functionality already performs strongly in areas like forecasting, recognition, event detection, personalization, interaction support, recommendations, and goal-driven optimization," she states. "Good business areas to identify a potential use case could therefore be in finance, customer service, marketing, cyber security, or stock control." Related:Strengthening Your Case Executives respond to proof, not promises, Mains says. "Instead of leading with research reports, I’ve found that real, industry-specific case studies are far more impactful," he observes. "If a direct competitor has successfully integrated AI into sales, marketing, or operations, use that example, because it creates urgency." Instead of just citing AI-driven efficiency gains, Mains recommends framing AI as a way to free-up leadership to focus on high-level strategy rather than day-to-day operations. Instead of trying to pitch AI in broad terms, Mains advises aligning the technology to the company's stated goals. "If the company is struggling with customer retention, talk about how AI can improve personalization," he suggests. "If operational inefficiencies are a problem, highlight AI-driven automation." The moment AI is framed as a business enabler rather than a technology trend, the conversation shifts from resistance to curiosity. Related:When All Else Fails If leadership refuses to embrace AI, it’s important to document the cost of inaction, Mains says. "Keep track of inefficiencies, missed opportunities, and competitor advancements," he recommends. Sometimes, leadership only shifts when management’s view of the risks of staying stagnant outweigh the risks of change. "If a company refuses to innovate despite clear benefits, that’s a red flag for long-term growth." Final Thoughts For enterprises that have so far done little or nothing in the way of AI deployment, the technology may appear optional, McQuarrie observes. Yet soon, operating without AI will become as unthinkable as running a business without the internet. Enterprise leaders who delay AI adoption risk falling behind the competition. "The best approach is to embrace a mindset of humility and curiosity -- actively seek out knowledge, ask questions, and learn from peers who are already seeing AI’s impact," he says. "To stay competitive in this rapidly evolving landscape, leaders should start now." The best companies aren't just using AI to improve; they're using the technology to redefine how they do business, Mains says. Leaders who recognize AI as a business accelerator will be the ones leading their industries in the next decade. "Those who hesitate? They’ll be playing catch-up." he concludes. About the AuthorJohn EdwardsTechnology Journalist & AuthorJohn Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.See more from John EdwardsWebinarsMore WebinarsReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like