Ivy Grant, SVP of Strategy & Operations, Twilio June 13, 20255 Min Readpeshkova via alamy stockAsk technologists and enterprise leaders what they hope AI will deliver, and most will land on some iteration of the "T" word: transformation. No surprise, AI and its “cooler than you” cousin, generative AI (GenAI), have been hyped nonstop for the past 24 months. But therein lies the problem. Many organizations are rushing to implement AI without a grasp on the return on investment (ROI), leading to high spend and low impact. Without anchoring AI to clear friction points and acceleration opportunities, companies invite fatigue, anxiety and competitive risk. Two-thirds of C-suite execs say GenAI has created tension and division within their organizations; nearly half say it’s “tearing their company apart.” Most (71%) report adoption challenges; more than a third call it a massive disappointment. While AI's potential is irrefutable, companies need to reject the narrative of AI as a standalone strategy or transformational savior. Its true power is as a catalyst to amplify what already works and surface what could. Here are three principles to make that happen. 1. Start with friction, not function Many enterprises struggle with where to start when integrating AI. My advice: Start where the pain is greatest. Identify the processes that create the most friction and work backward from there. AI is a tool, not a solution. By mapping real pain points to AI use cases, you can hone investments to the ripest fruit rather than simply where it hangs at the lowest. Related:For example, one of our top sources of customer pain was troubleshooting undeliverable messages, which forced users to sift through error code documentation. To solve this, an AI assistant was introduced to detect anomalies, explain causes in natural language, and guide customers toward resolution. We achieved a 97% real-time resolution rate through a blend of conversational AI and live support. Most companies have long-standing friction points that support teams routinely explain. Or that you’ve developed organizational calluses over; problems considered “just the cost of doing business.” GenAI allows leaders to revisit these areas and reimagine what’s possible. 2. The need for (dual) speed We hear stories of leaders pushing an “all or nothing” version of AI transformation: Use AI to cut functional headcount or die. Rather than leading with a “stick” through wholesale transformation mandates or threats to budgets, we must recognize AI implementation as a fundamental culture change. Just as you wouldn't expect to transform your company culture overnight by edict, it's unreasonable to expect something different from your AI transformation. Related:Some leaders have a tendency to move faster than the innovation ability or comfort level of their people. Most functional leads aren’t obstinate in their slow adoption of AI tools, their long-held beliefs to run a process or to assess risks. We hired these leaders for their decades of experience in “what good looks like” and deep expertise in incremental improvements; then we expect them to suddenly define a futuristic vision that challenges their own beliefs. As executive leaders, we must give grace, space and plenty of “carrots” -- incentives, training, and support resources -- to help them reimagine complex workflows with AI. And, we must recognize that AI has the ability to make progress in ways that may not immediately create cost efficiencies, such as for operational improvements that require data cleansing, deep analytics, forecasting, dynamic pricing, and signal sensing. These aren’t the sexy parts of AI, but they’re the types of issues that require superhuman intelligence and complex problem-solving that AI was made for. 3. A flywheel of acceleration The other transformation that AI should support is creating faster and broader “test and learn” cycles. AI implementation is not a linear process with start here and end there. Organizations that want to leverage AI as a competitive advantage should establish use cases where AI can break down company silos and act as a catalyst to identify the next opportunity. That identifies the next as a flywheel of acceleration. This flywheel builds on accumulated learnings, making small successes into larger wins while avoiding costly AI disasters from rushed implementation. Related:For example, at Twilio we are building a customer intelligence platform that analyzes thousands of conversations to identify patterns and drive insights. If we see multiple customers mention a competitor's pricing, it could signal a take-out campaign. What once took weeks to recognize and escalate can now be done in near real-time and used for highly coordinated activations across marketing, product, sales, and other teams. With every AI acceleration win, we uncover more places to improve hand-offs, activation speed, and business decision-making. That flywheel of innovation is how true AI transformation begins to drive impactful business outcomes. Ideas to Fuel Your AI Strategy Organizations can accelerate their AI implementations through these simple shifts in approach: Revisit your long-standing friction points, both customer-facing and internal, across your organization -- particularly explore the ones you thought were “the cost of doing business” Don’t just look for where AI can reduce manual processes, but find the highly complex problems and start experimenting Support your functional experts with AI-driven training, resources, tools, and incentives to help them challenge their long-held beliefs about what works for the future Treat AI implementation as a cultural change that requires time, experimentation, learning, and carrots (not just sticks) Recognize that transformation starts with a flywheel of acceleration, where each new experiment can lead to the next big discovery The most impactful AI implementations don’t rush transformation; they strategically accelerate core capabilities and unlock new ones to drive measurable change. About the AuthorIvy GrantSVP of Strategy & Operations, Twilio Ivy Grant is Senior Vice President of Strategy & Operations at Twilio where she leads strategic planning, enterprise analytics, M&A Integration and is responsible for driving transformational initiatives that enable Twilio to continuously improve its operations. Prior to Twilio, Ivy’s career has balanced senior roles in strategy consulting at McKinsey & Company, Edelman and PwC with customer-centric operational roles at Walmart, Polo Ralph Lauren and tech startup Eversight Labs. She loves solo international travel, hugging exotic animals and boxing. Ivy has an MBA from NYU’s Stern School of Business and a BS in Applied Economics from Cornell University. See more from Ivy GrantReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like

Last year, MACK Books published Architecture from Below, which anthologized writings by the French Brazilian architect, theorist, and painter Sérgio Ferro. (Douglas Spencer reviewed it for AN.) Now, MACK follows with Design and the Building Site and Complementary Essays, the second in the trilogy of books dedicated to Ferro’s scholarship. The following excerpt of the author’s 2023 preface to the English edition, which preserves its British phrasing, captures Ferro’s realization about the working conditions of construction sites in Brasília. The sentiment is likely relatable even today for young architects as they discover how drawings become buildings. Design and the Building Site and Complementary Essays will be released on May 22. If I remember correctly, it was in 1958 or 1959, when Rodrigo and I were second- or third year architecture students at FAUUSP, that my father, the real estate developer Armando Simone Pereira, commissioned us to design two large office buildings and eleven shops in Brasilia, which was then under construction. Of course, we were not adequately prepared for such an undertaking. Fortunately, Oscar Niemeyer and his team, who were responsible for overseeing the construction of the capital, had drawn up a detailed document determining the essential characteristics of all the private sector buildings. We followed these prescriptions to the letter, which saved us from disaster. Nowadays, it is hard to imagine the degree to which the construction of Brasilia inspired enthusiasm and professional pride in the country’s architects. And in the national imagination, the city’s establishment in the supposedly unpopulated hinterland evoked a re-founding of Brazil. Up until that point, the occupation of our immense territory had been reduced to a collection of arborescent communication routes, generally converging upon some river, following it up to the Atlantic Ocean. Through its ports, agricultural or extractive commodities produced by enslaved peoples or their substitutes passed towards the metropolises; goods were exchanged in the metropolises for more elaborate products, which took the opposite route. Our national identity was summed up in a few symbols, such as the anthem or the flag, and this scattering of paths pointing overseas. Brasilia would radically change this situation, or so we believed. It would create a central hub where the internal communication routes could converge, linking together hithertoseparate junctions, stimulating trade and economic progress in the country’s interior. It was as if, for the first time, we were taking care of ourselves. At the nucleus of this centripetal movement, architecture would embody the renaissance. And at the naval of the nucleus, the symbolic mandala of this utopia: the cathedral. Rodrigo and I got caught up in the euphoria. And perhaps more so than our colleagues, because we were taking part in the adventure with ‘our’ designs. The reality was very different — but we did not know that yet. At that time, architects in Brazil were responsible for verifying that the construction was in line with the design. We had already monitored some of our first building sites. But the construction company in charge of them, Osmar Souza e Silva’s CENPLA, specialized in the building sites of modernist architects from the so-called Escola Paulista led by Vilanova Artigas (which we aspired to be a part of, like the pretentious students we were). Osmar was very attentive to his clients and his workers, who formed a supportive and helpful team. He was even more careful with us, because he knew how inexperienced we were. I believe that the CENPLA was particularly important in São Paulo modernism: with its congeniality, it facilitated experimentation, but for the same reason, it deceived novices like us about the reality of other building sites. Consequently, Rodrigo and I travelled to Brasilia several times to check that the constructions followed ‘our’ designs and to resolve any issues. From the very first trip, our little bubble burst. Our building sites, like all the others in the future capital, bore no relation to Osmar’s. They were more like a branch of hell. A huge, muddy wasteland, in which a few cranes, pile drivers, tractors, and excavators dotted the mound of scaffolding occupied by thousands of skinny, seemingly exhausted wretches, who were nevertheless driven on by the shouts of master builders and foremen, in turn pressured by the imminence of the fateful inauguration date. Surrounding or huddled underneath the marquees of buildings under construction, entire families, equally skeletal and ragged, were waiting for some accident or death to open up a vacancy. In contact only with the master builders, and under close surveillance so we would not speak to the workers, we were not allowed to see what comrades who had worked on these sites later told us in prison: suicide abounded; escape was known to be futile in the unpopulated surroundings with no viable roads; fatal accidents were often caused by weakness due to chronic diarrhoea, brought on by rotten food that came from far away; outright theft took place in the calculation of wages and expenses in the contractor’s grocery store; camps were surrounded by law enforcement. I repeat this anecdote yet again not to invoke the benevolence of potential readers, but rather to point out the conditions that, in my opinion, allowed two students (Flávio Império joined us a little later) still in their professional infancy to quickly adopt positions that were contrary to the usual stance of architects. As the project was more Oscar Niemeyer’s than it was our own, we did not have the same emotional attachment that is understandably engendered between real authors and their designs. We had not yet been imbued with the charm and aura of the métier. And the only building sites we had visited thus far, Osmar’s, were incomparable to those we discovered in Brasilia. In short, our youthfulness and unpreparedness up against an unbearable situation made us react almost immediately to the profession’s satisfied doxa. Unprepared and young perhaps, but already with Marx by our side. Rodrigo and I joined the student cell of the Brazilian Communist Party during our first year at university. In itself, this did not help us much: the Party’s Marxism, revised in the interests of the USSR, was pitiful. Even high-level leaders rarely went beyond the first chapter of Capital. But at the end of the 1950s, the effervescence of the years to come was already nascent:  […] this extraordinary revival […] the rediscovery of Marxism and the great dialectical texts and traditions in the 1960s: an excitement that identifies a forgotten or repressed moment of the past as the new and subversive, and learns the dialectical grammar of a Hegel or an Adorno, a Marx or a Lukács, like a foreign language that has resources unavailable in our own. And what is more: the Chinese and Cuban revolutions, the war in Vietnam, guerrilla warfare of all kinds, national liberation movements, and a rare libertarian disposition in contemporary history, totally averse to fanaticism and respect for ideological apparatuses of (any) state or institution. Going against the grain was almost the norm. We were of course no more than contemporaries of our time. We were soon able to position ourselves from chapters 13, 14, and 15 of Capital, but only because we could constantly cross-reference Marx with our observations from well-contrasted building sites and do our own experimenting. As soon as we identified construction as manufacture, for example, thanks to the willingness and even encouragement of two friends and clients, Boris Fausto and Bernardo Issler, I was able to test both types of manufacture — organic and heterogeneous — on similar-sized projects taking place simultaneously, in order to find out which would be most convenient for the situation in Brazil, particularly in São Paulo. Despite the scientific shortcomings of these tests, they sufficed for us to select organic manufacture. Arquitetura Nova had defined its line of practice, studies, and research. There were other sources that were central to our theory and practice. Flávio Império was one of the founders of the Teatro de Arena, undoubtedly the vanguard of popular, militant theatre in Brazil. He won practically every set design award. He brought us his marvelous findings in spatial condensation and malleability, and in the creative diversion of techniques and material—appropriate devices for an underdeveloped country. This is what helped us pave the way to reformulating the reigning design paradigms.  We had to do what Flávio had done in the theatre: thoroughly rethink how to be an architect. Upend the perspective. The way we were taught was to start from a desired result; then others would take care of getting there, no matter how. We, on the other hand, set out to go down to the building site and accompany those carrying out the labor itself, those who actually build, the formally subsumed workers in manufacture who are increasingly deprived of the knowledge and know-how presupposed by this kind of subsumption. We should have been fostering the reconstitution of this knowledge and know-how—not so as to fulfil this assumption, but in order to reinvigorate the other side of this assumption according to Marx: the historical rebellion of the manufacture worker, especially the construction worker. We had to rekindle the demand that fueled this rebellion: total self-determination, and not just that of the manual operation as such. Our aim was above all political and ethical. Aesthetics only mattered by way of what it included—ethics. Instead of estética, we wrote est ética [this is ethics]. We wanted to make building sites into nests for the return of revolutionary syndicalism, which we ourselves had yet to discover. Sérgio Ferro, born in Brazil in 1938, studied architecture at FAUUSP, São Paulo. In the 1960s, he joined the Brazilian communist party and started, along with Rodrigo Lefevre and Flávio Império, the collective known as Arquitetura Nova. After being arrested by the military dictatorship that took power in Brazil in 1964, he moved to France as an exile. As a painter and a professor at the École Nationale Supérieure d’Architecture de Grenoble, where he founded the Dessin/Chantier laboratory, he engaged in extensive research which resulted in several publications, exhibitions, and awards in Brazil and in France, including the title of Chevalier des Arts et des Lettres in 1992. Following his retirement from teaching, Ferro continues to research, write, and paint.

Ivy Grant, SVP of Strategy & Operations, Twilio June 13, 20255 Min Readpeshkova via alamy stockAsk technologists and enterprise leaders what they hope AI will deliver, and most will land on some iteration of the "T" word: transformation. No surprise, AI and its “cooler than you” cousin, generative AI (GenAI), have been hyped nonstop for the past 24 months. But therein lies the problem. Many organizations are rushing to implement AI without a grasp on the return on investment (ROI), leading to high spend and low impact. Without anchoring AI to clear friction points and acceleration opportunities, companies invite fatigue, anxiety and competitive risk. Two-thirds of C-suite execs say GenAI has created tension and division within their organizations; nearly half say it’s “tearing their company apart.” Most (71%) report adoption challenges; more than a third call it a massive disappointment. While AI's potential is irrefutable, companies need to reject the narrative of AI as a standalone strategy or transformational savior. Its true power is as a catalyst to amplify what already works and surface what could. Here are three principles to make that happen. 1. Start with friction, not function Many enterprises struggle with where to start when integrating AI. My advice: Start where the pain is greatest. Identify the processes that create the most friction and work backward from there. AI is a tool, not a solution. By mapping real pain points to AI use cases, you can hone investments to the ripest fruit rather than simply where it hangs at the lowest. Related:For example, one of our top sources of customer pain was troubleshooting undeliverable messages, which forced users to sift through error code documentation. To solve this, an AI assistant was introduced to detect anomalies, explain causes in natural language, and guide customers toward resolution. We achieved a 97% real-time resolution rate through a blend of conversational AI and live support. Most companies have long-standing friction points that support teams routinely explain. Or that you’ve developed organizational calluses over; problems considered “just the cost of doing business.” GenAI allows leaders to revisit these areas and reimagine what’s possible. 2. The need for (dual) speed We hear stories of leaders pushing an “all or nothing” version of AI transformation: Use AI to cut functional headcount or die. Rather than leading with a “stick” through wholesale transformation mandates or threats to budgets, we must recognize AI implementation as a fundamental culture change. Just as you wouldn't expect to transform your company culture overnight by edict, it's unreasonable to expect something different from your AI transformation. Related:Some leaders have a tendency to move faster than the innovation ability or comfort level of their people. Most functional leads aren’t obstinate in their slow adoption of AI tools, their long-held beliefs to run a process or to assess risks. We hired these leaders for their decades of experience in “what good looks like” and deep expertise in incremental improvements; then we expect them to suddenly define a futuristic vision that challenges their own beliefs. As executive leaders, we must give grace, space and plenty of “carrots” -- incentives, training, and support resources -- to help them reimagine complex workflows with AI. And, we must recognize that AI has the ability to make progress in ways that may not immediately create cost efficiencies, such as for operational improvements that require data cleansing, deep analytics, forecasting, dynamic pricing, and signal sensing. These aren’t the sexy parts of AI, but they’re the types of issues that require superhuman intelligence and complex problem-solving that AI was made for. 3. A flywheel of acceleration The other transformation that AI should support is creating faster and broader “test and learn” cycles. AI implementation is not a linear process with start here and end there. Organizations that want to leverage AI as a competitive advantage should establish use cases where AI can break down company silos and act as a catalyst to identify the next opportunity. That identifies the next as a flywheel of acceleration. This flywheel builds on accumulated learnings, making small successes into larger wins while avoiding costly AI disasters from rushed implementation. Related:For example, at Twilio we are building a customer intelligence platform that analyzes thousands of conversations to identify patterns and drive insights. If we see multiple customers mention a competitor's pricing, it could signal a take-out campaign. What once took weeks to recognize and escalate can now be done in near real-time and used for highly coordinated activations across marketing, product, sales, and other teams. With every AI acceleration win, we uncover more places to improve hand-offs, activation speed, and business decision-making. That flywheel of innovation is how true AI transformation begins to drive impactful business outcomes. Ideas to Fuel Your AI Strategy Organizations can accelerate their AI implementations through these simple shifts in approach: Revisit your long-standing friction points, both customer-facing and internal, across your organization -- particularly explore the ones you thought were “the cost of doing business” Don’t just look for where AI can reduce manual processes, but find the highly complex problems and start experimenting Support your functional experts with AI-driven training, resources, tools, and incentives to help them challenge their long-held beliefs about what works for the future Treat AI implementation as a cultural change that requires time, experimentation, learning, and carrots (not just sticks) Recognize that transformation starts with a flywheel of acceleration, where each new experiment can lead to the next big discovery The most impactful AI implementations don’t rush transformation; they strategically accelerate core capabilities and unlock new ones to drive measurable change. About the AuthorIvy GrantSVP of Strategy & Operations, Twilio Ivy Grant is Senior Vice President of Strategy & Operations at Twilio where she leads strategic planning, enterprise analytics, M&A Integration and is responsible for driving transformational initiatives that enable Twilio to continuously improve its operations. Prior to Twilio, Ivy’s career has balanced senior roles in strategy consulting at McKinsey & Company, Edelman and PwC with customer-centric operational roles at Walmart, Polo Ralph Lauren and tech startup Eversight Labs. She loves solo international travel, hugging exotic animals and boxing. Ivy has an MBA from NYU’s Stern School of Business and a BS in Applied Economics from Cornell University. See more from Ivy GrantReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like

As AI faces court challenges from Disney and Universal, legal battles are shaping the industry's future | Opinion Silicon advances and design innovations do still push us forward – but the future landscape of the industry is also being sculpted in courtrooms and parliaments Image credit: Disney / Epic Games Opinion by Rob Fahey Contributing Editor Published on June 13, 2025 In some regards, the past couple of weeks have felt rather reassuring. We've just seen a hugely successful launch for a new Nintendo console, replete with long queues for midnight sales events. Over the next few days, the various summer events and showcases that have sprouted amongst the scattered bones of E3 generated waves of interest and hype for a host of new games. It all feels like old times. It's enough to make you imagine that while change is the only constant, at least it's we're facing change that's fairly well understood, change in the form of faster, cheaper silicon, or bigger, more ambitious games. If only the winds that blow through this industry all came from such well-defined points on the compass. Nestled in amongst the week's headlines, though, was something that's likely to have profound but much harder to understand impacts on this industry and many others over the coming years – a lawsuit being brought by Disney and NBC Universal against Midjourney, operators of the eponymous generative AI image creation tool. In some regards, the lawsuit looks fairly straightforward; the arguments made and considered in reaching its outcome, though, may have a profound impact on both the ability of creatives and media companies (including game studios and publishers) to protect their IP rights from a very new kind of threat, and the ways in which a promising but highly controversial and risky new set of development and creative tools can be used commercially. A more likely tack on Midjourney's side will be the argument that they are not responsible for what their customers create with the tool I say the lawsuit looks straightforward from some angles, but honestly overall it looks fairly open and shut – the media giants accuse Midjourney of replicating their copyrighted characters and material, and of essentially building a machine for churning out limitless copyright violations. The evidence submitted includes screenshot after screenshot of Midjourney generating pages of images of famous copyrighted and trademarked characters ranging from Yoda to Homer Simpson, so "no we didn't" isn't going to be much of a defence strategy here. A more likely tack on Midjourney's side will be the argument that they are not responsible for what their customers create with the tool – you don't sue the manufacturers of oil paints or canvases when artists use them to paint something copyright-infringing, nor does Microsoft get sued when someone writes something libellous in Word, and Midjourney may try to argue that their software belongs in that tool category, with users alone being ultimately responsible for how they use them. If that argument prevails and survives appeals and challenges, it would be a major triumph for the nascent generative AI industry and a hugely damaging blow to IP holders and creatives, since it would seriously undermine their argument that AI companies shouldn't be able to include copyrighted material into training data sets without licensing or compensation. The reason Disney and NBCU are going after Midjourney specifically seems to be partially down to Midjourney being especially reticent to negotiate with them about licensing fees and prompt restrictions; other generative AI firms have started talking, at least, about paying for content licenses for training data, and have imposed various limitations on their software to prevent the most egregious and obvious forms of copyright violation (at least for famous characters belonging to rich companies; if you're an individual or a smaller company, it's entirely the Wild West out there as regards your IP rights). In the process, though, they're essentially risking a court showdown over a set of not-quite-clear legal questions at the heart of this dispute, and if Midjourney were to prevail in that argument, other AI companies would likely back off from engaging with IP holders on this topic. To be clear, though, it seems highly unlikely that Midjourney will win that argument, at least not in the medium to long term. Yet depending on how this case moves forward, losing the argument could have equally dramatic consequences – especially if the courts find themselves compelled to consider the question of how, exactly, a generative AI system reproduces a copyrighted character with such precision without storing copyright-infringing data in some manner. The 2020s are turning out to be the decade in which many key regulatory issues come to a head all at once AI advocates have been trying to handwave around this notion from the outset, but at some point a court is going to have to sit down and confront the fact that the precision with which these systems can replicate copyrighted characters, scenes, and other materials requires that they must have stored that infringing material in some form. That it's stored as a scattered mesh of probabilities across the vertices of a high-dimensional vector array, rather than a straightforward, monolithic media file, is clearly important but may ultimately be considered moot. If the data is in the system and can be replicated on request, how that differs from Napster or The Pirate Bay is arguably just a matter of technical obfuscation. Not having to defend that technical argument in court thus far has been a huge boon to the generative AI field; if it is knocked over in that venue, it will have knock-on effects on every company in the sector and on every business that uses their products. Nobody can be quite sure which of the various rocks and pebbles being kicked on this slope is going to set off the landslide, but there seems to be an increasing consensus that a legal and regulatory reckoning is coming for generative AI. Consequently, a lot of what's happening in that market right now has the feel of companies desperately trying to establish products and lock in revenue streams before that happens, because it'll be harder to regulate a technology that's genuinely integrated into the world's economic systems than it is to impose limits on one that's currently only clocking up relatively paltry sales and revenues. Keeping an eye on this is crucial for any industry that's started experimenting with AI in its workflows – none more than a creative industry like video games, where various forms of AI usage have been posited, although the enthusiasm and buzz so far massively outweighs any tangible benefits from the technology. Regardless of what happens in legal and regulatory contexts, AI is already a double-edged sword for any creative industry. Used judiciously, it might help to speed up development processes and reduce overheads. Applied in a slapdash or thoughtless manner, it can and will end up wreaking havoc on development timelines, filling up storefronts with endless waves of vaguely-copyright-infringing slop, and potentially make creative firms, from the industry's biggest companies to its smallest indie developers, into victims of impossibly large-scale copyright infringement rather than beneficiaries of a new wave of technology-fuelled productivity. The legal threat now hanging over the sector isn't new, merely amplified. We've known for a long time that AI generated artwork, code, and text has significant problems from the perspective of intellectual property rights (you can infringe someone else's copyright with it, but generally can't impose your own copyright on its creations – opening careless companies up to a risk of having key assets in their game being technically public domain and impossible to protect). Even if you're not using AI yourself, however – even if you're vehemently opposed to it on moral and ethical grounds (which is entirely valid given the highly dubious land-grab these companies have done for their training data), the Midjourney judgement and its fallout may well impact the creative work you produce yourself and how it ends up being used and abused by these products in future. This all has huge ramifications for the games business and will shape everything from how games are created to how IP can be protected for many years to come – a wind of change that's very different and vastly more unpredictable than those we're accustomed to. It's a reminder of just how much of the industry's future is currently being shaped not in development studios and semiconductor labs, but rather in courtrooms and parliamentary committees. The ways in which generative AI can be used and how copyright can persist in the face of it will be fundamentally shaped in courts and parliaments, but it's far from the only crucially important topic being hashed out in those venues. The ongoing legal turmoil over the opening up of mobile app ecosystems, too, will have huge impacts on the games industry. Meanwhile, the debates over loot boxes, gambling, and various consumer protection aspects related to free-to-play models continue to rumble on in the background. Because the industry moves fast while governments move slow, it's easy to forget that that's still an active topic for as far as governments are concerned, and hammers may come down at any time. Regulation by governments, whether through the passage of new legislation or the interpretation of existing laws in the courts, has always loomed in the background of any major industry, especially one with strong cultural relevance. The games industry is no stranger to that being part of the background heartbeat of the business. The 2020s, however, are turning out to be the decade in which many key regulatory issues come to a head all at once, whether it's AI and copyright, app stores and walled gardens, or loot boxes and IAP-based business models. Rulings on those topics in various different global markets will create a complex new landscape that will shape the winds that blow through the business, and how things look in the 2030s and beyond will be fundamentally impacted by those decisions.

에이전틱 AI는 아직 초기 단계이지만, 많은 기업이 AI 에이전트를 빠르게 도입하고 있다. 여기에는 두 기술의 차이에 대한 혼란이 발생하고 있다. 많은 사람이 ‘에이전틱 AI’와 ‘AI 에이전트’라는 용어를 같은 의미로 사용해왔지만, 이 둘이 별개의 기술이자 상호 연관된 도구라는 인식이 점차 확산되고 있다. 전문가들은 CIO가 적합한 기술을 올바른 목적에 맞게 사용하기 위해서는 이 둘의 차이를 이해

People are sharing Meta AI prompts that are not intended for the public.

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The Conductor Junction Evolution is a brand new paid upgrade in EA FC 25, and it allows you to reinforce your midfield. Costing 100,000 coins, it's not exactly cheap, even at this stage of the game. That said, the evolution offers substantial im