The Swedish brand lets the sleep do the talking.

The Hulk Hogan sex tape lawsuit, financed by a guy who flinches at the prospect of humanity enduring, is not really my story to tell. I was merely an observer at the time. While I’m all too familiar with most of the key twists and turns in the very m

The ROG Xbox Ally range has been developed by Microsoft in collaboration with Asus.

Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to $631 billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least $1 million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle.(Image source: Unsplash)

The recent wave of cyber attacks targeting UK retailers has been a moment of reckoning for the entire retail industry. As someone who went through supporting one of the largest retail breaches in history, this news hits close to home. The National Cyber Security Centre’s (NCSC) call to strengthen IT support protocols reinforces a hard truth: cybersecurity is no longer just a technical/operational issue. It’s a business issue that directly affects revenue, customer trust, and brand reputation. Retailers today are navigating an increasingly complex threat landscape, while also managing a vast user base that needs to stay informed and secure. The recent attacks don’t represent a failure, but an opportunity - an inflection point to invest in stronger visibility, continuous monitoring and a culture of shared responsibility that meets the realities of modern retail. We know that the cyber groups responsible for the recent retail hacks used sophisticated social engineering techniques, such as impersonating employees to deceive IT help desks into resetting passwords and providing information, thereby gaining unauthorised access to internal systems. Employees are increasingly a target, and retailers employ some of the largest, most diverse workforces, making them an even bigger risk with countless touchpoints for breaches. In these organisations, a cybersecurity-first culture is vital to combatting threats. Cybersecurity-first culture includes employees that are aware of these types of attacks and understand how to report them if they are contacted. In order to establish a cybersecurity-first culture, employees must be empowered to recognise and respond to threats, not just avoid them. This can be done through simulation training and threat assessments - showcasing real life examples of threats and brainstorming possible solutions to control and prevent further and future damage. This allows security teams to focus on strategy instead of constant firefighting, while leadership support - through budget, tools, and tone - reinforces its importance at every level. In addition to support workers, vendors also pose a significant attack path for bad actors. According to data from Elastic Path, 42% of retailers admit that legacy technology could be leaving them exposed to cyber risks. And with the accelerating pace of innovation, modern cyber threats are not only more complex, but often enter through unexpected avenues, like third-party vendors. Research from Vanta shows 46% of organisations say that a vendor of theirs has experienced a data breach since they started working together. The M&S breach is a case in point, with it being reported that attackers exploited a vulnerability in a contractor’s systems, not the retailer’s own. This underscores that visibility must extend beyond your perimeter to encompass the entire digital supply chain, in real time. Threats don’t wait for your quarterly review or annual audit. If you're only checking your controls or vendor status once a year, you're already behind. This means real-time visibility is now foundational to cyber defence. We need to know when something changes the moment it happens. This can be done through continuous monitoring, both for the technical controls and the relationships that introduce risk into your environment. We also need to rethink the way we resource and prioritise that visibility. Manual processes don’t scale with the complexity of modern infrastructure. Automation and tooling can help surface the right signals from the noise - whether it’s misconfigurations, access drift, or suspicious vendor behavior. The best case scenario is that security measures are embedded into all digital architecture, utilising a few security ‘must haves’ such as secure coding, continuous monitoring, and regular testing and improvement. Retailers who want to get proactive and about breaches following the events of the last few weeks can follow this action plan to get started: First, awareness - have your security leadership send a message out to managers of help desks and support teams to make sure they are aware of the recent attacks on retailers, and are in a position to inform teams of what to look out for. Then, investigate - pinpoint the attack path used on other retailers to make sure you have a full understanding of the risk to your organisation. After that, assess - conduct a threat assessment to identify what could go wrong, or how this attack path could be used in your organisation. The final step is to identify - figure out the highest risk gaps in your organisation, and the remediation steps to address each one. Strong cybersecurity doesn’t come from quick fixes - it takes time, leadership buy-in, and a shift in mindset across the organisation. My advice to security teams is simple: speak in outcomes. Frame cyber risk as business risk, because that’s what it is. The retailers that have fallen victim to recent attacks are facing huge financial losses, which makes this not just an IT issue - it’s a boardroom issue. Customers are paying attention. They want to trust the brands they buy from, and that trust is built on transparency and preparation. The recent retail attacks aren’t a reason to panic - they’re a reason to reset, evaluate current state risks, and fully understand the potential impacts of what is happening elsewhere. This is the moment to invest in your infrastructure, empower your teams, and embed security into your operations. The organisations that do this now won’t just be safer - they’ll be more competitive, more resilient, and better positioned for whatever comes next. Jadee Hanson is the Chief Information Security Officer at Vanta Read more about cyber security in retail Content Goes Here Harrods becomes latest UK retailer to fall victim to cyber attack Retail cyber crime spree a ‘wake-up call’, says NCSC CEO Retail cyber attacks hit food distributor Peter Green Chilled

For the past two years, it’s been a ghost in the machine of American tech. Between 2022 and today, a little-noticed tweak to the U.S. tax code has quietly rewired the financial logic of how American companies invest in research and development. Outside of CFO and accounting circles, almost no one knew it existed. “I work on these tax write-offs and still hadn’t heard about this,” a chief operating officer at a private-equity-backed tech company told Quartz. “It’s just been so weirdly silent.”AdvertisementStill, the delayed change to a decades-old tax provision — buried deep in the 2017 tax law — has contributed to the loss of hundreds of thousands of high-paying, white-collar jobs. That’s the picture that emerges from a review of corporate filings, public financial data, analysis of timelines, and interviews with industry insiders. One accountant, working in-house at a tech company, described it as a “niche issue with broad impact,” echoing sentiments from venture capital investors also interviewed for this article. Some spoke on condition of anonymity to discuss sensitive political matters.Since the start of 2023, more than half-a-million tech workers have been laid off, according to industry tallies. Headlines have blamed over-hiring during the pandemic and, more recently, AI. But beneath the surface was a hidden accelerant: a change to what’s known as Section 174 that helped gut in-house software and product development teams everywhere from tech giants such as Microsoft (MSFT) and Meta (META) to much smaller, private, direct-to-consumer and other internet-first companies.Now, as a bipartisan effort to repeal the Section 174 change moves through Congress, bigger questions are surfacing: How did a single line in the tax code help trigger a tsunami of mass layoffs? And why did no one see it coming? For almost 70 years, American companies could deduct 100% of qualified research and development spending in the year they incurred the costs. Salaries, software, contractor payments — if it contributed to creating or improving a product, it came off the top of a firm’s taxable income.AdvertisementThe deduction was guaranteed by Section 174 of the IRS Code of 1954, and under the provision, R&D flourished in the U.S.Microsoft was founded in 1975. Apple (AAPL) launched its first computer in 1976. Google (GOOGL) incorporated in 1998. Facebook opened to the general public in 2006. All these companies, now among the most valuable in the world, developed their earliest products — programming tools, hardware, search engines — under a tax system that rewarded building now, not later.The subsequent rise of smartphones, cloud computing, and mobile apps also happened in an America where companies could immediately write off their investments in engineering, infrastructure, and experimentation. It was a baseline assumption — innovation and risk-taking subsidized by the tax code — that shaped how founders operated and how investors made decisions.In turn, tech companies largely built their products in the U.S. AdvertisementMicrosoft’s operating systems were coded in Washington state. Apple’s early hardware and software teams were in California. Google’s search engine was born at Stanford and scaled from Mountain View. Facebook’s entire social architecture was developed in Menlo Park. The deduction directly incentivized keeping R&D close to home, rewarding companies for investing in American workers, engineers, and infrastructure.That’s what makes the politics of Section 174 so revealing. For all the rhetoric about bringing jobs back and making things in America, the first Trump administration’s major tax bill arguably helped accomplish the opposite.When Congress passed the Tax Cuts and Jobs Act (TCJA), the signature legislative achievement of President Donald Trump’s first term, it slashed the corporate tax rate from 35% to 21% — a massive revenue loss on paper for the federal government.To make the 2017 bill comply with Senate budget rules, lawmakers needed to offset the cost. So they added future tax hikes that wouldn’t kick in right away, wouldn’t provoke immediate backlash from businesses, and could, in theory, be quietly repealed later.AdvertisementThe delayed change to Section 174 — from immediate expensing of R&D to mandatory amortization, meaning that companies must spread the deduction out in smaller chunks over five or even 15-year periods — was that kind of provision. It didn’t start affecting the budget until 2022, but it helped the TCJA appear “deficit neutral” over the 10-year window used for legislative scoring.The delay wasn’t a technical necessity. It was a political tactic. Such moves are common in tax legislation. Phase-ins and delayed provisions let lawmakers game how the Congressional Budget Office (CBO) — Congress’ nonpartisan analyst of how bills impact budgets and deficits — scores legislation, pushing costs or revenue losses outside official forecasting windows.And so, on schedule in 2022, the change to Section 174 went into effect. Companies filed their 2022 tax returns under the new rules in early 2023. And suddenly, R&D wasn’t a full, immediate write-off anymore. The tax benefits of salaries for engineers, product and project managers, data scientists, and even some user experience and marketing staff — all of which had previously reduced taxable income in year one — now had to be spread out over five- or 15-year periods. To understand the impact, imagine a personal tax code change that allowed you to deduct 100% of your biggest source of expenses, and that becoming a 20% deduction. For cash-strapped companies, especially those not yet profitable, the result was a painful tax bill just as venture funding dried up and interest rates soared.AdvertisementSalesforce office buildings in San Francisco.Photo: Jason Henry/Bloomberg (Getty Images)It’s no coincidence that Meta announced its “Year of Efficiency” immediately after the Section 174 change took effect. Ditto Microsoft laying off 10,000 employees in January 2023 despite strong earnings, or Google parent Alphabet cutting 12,000 jobs around the same time.Amazon (AMZN) also laid off almost 30,000 people, with cuts focused not just on logistics but on Alexa and internal cloud tools — precisely the kinds of projects that would have once qualified as immediately deductible R&D. Salesforce (CRM) eliminated 10% of its staff, or 8,000 people, including entire product teams.In public, companies blamed bloat and AI. But inside boardrooms, spreadsheets were telling a quieter story. And MD&A notes — management’s notes on the numbers — buried deep in 10-K filings recorded the change, too. R&D had become more expensive to carry. Headcount, the leading R&D expense across the tech industry, was the easiest thing to cut.AdvertisementIn its 2023 annual report, Meta described salaries as its single biggest R&D expense. Between the first and second years that the Section 174 change began affecting tax returns, Meta cut its total workforce by almost 25%. Over the same period, Microsoft reduced its global headcount by about 7%, with cuts concentrated in product-facing, engineering-heavy roles.Smaller companies without the fortress-like balance sheets of Big Tech have arguably been hit even harder. Twilio (TWLO) slashed 22% of its workforce in 2023 alone. Shopify (SHOP) (headquartered in Canada but with much of its R&D teams in the U.S.) cut almost 30% of staff in 2022 and 2023. Coinbase (COIN) reduced headcount by 36% across a pair of brutal restructuring waves.Since going into effect, the provision has hit at the very heart of America’s economic growth engine: the tech sector.By market cap, tech giants dominate the S&P 500, with the “Magnificent 7” alone accounting for more than a third of the index’s total value. Workforce numbers tell a similar story, with tech employing millions of Americans directly and supporting the employment of tens of millions more. As measured by GDP, capital-T tech contributes about 10% of national output.AdvertisementIt’s not just that tech layoffs were large, it’s that they were massively disproportionate. Across the broader U.S. economy, job cuts hovered around in low single digits across most sectors. But in tech, entire divisions vanished, with a whopping 60% jump in layoffs between 2022 and 2023. Some cuts reflected real inefficiencies — a response to over-hiring during the zero-interest rate boom. At the same time, many of the roles eliminated were in R&D, product, and engineering, precisely the kind of functions that had once benefitted from generous tax treatment under Section 174.Throughout the 2010s, a broad swath of startups, direct-to-consumer brands, and internet-first firms — basically every company you recognize from Instagram or Facebook ads — built their growth models around a kind of engineered break-even.The tax code allowed them to spend aggressively on product and engineering, then write it all off as R&D, keeping their taxable income close to zero by design. It worked because taxable income and actual cash flow were often notGAAP accounting practices. Basically, as long as spending counted as R&D, companies could report losses to investors while owing almost nothing to the IRS.But the Section 174 change broke that model. Once those same expenses had to be spread out, or amortized, over multiple years, the tax shield vanished. Companies that were still burning cash suddenly looked profitable on paper, triggering real tax bills on imaginary gains.AdvertisementThe logic that once fueled a generation of digital-first growth collapsed overnight.So it wasn’t just tech experiencing effects. From 1954 until 2022, the U.S. tax code had encouraged businesses of all stripes to behave like tech companies. From retail to logistics, healthcare to media, if firms built internal tools, customized a software stack, or invested in business intelligence and data-driven product development, they could expense those costs. The write-off incentivized in-house builds and fast growth well outside the capital-T tech sector. This lines up with OECD research showing that immediate deductions foster innovation more than spread-out ones.And American companies ran with that logic. According to government data, U.S. businesses reported about $500 billion in R&D expenditures in 2019 alone, and almost half of that came from industries outside traditional tech. The Bureau of Economic Analysis estimates that this sector, the broader digital economy, accounts for another 10% of GDP.Add that to core tech’s contribution, and the Section 174 shift has likely touched at least 20% of the U.S. economy.AdvertisementThe result? A tax policy aimed at raising short-term revenue effectively hid a time bomb inside the growth engines of thousands of companies. And when it detonated, it kneecapped the incentive for hiring American engineers or investing in American-made tech and digital products.It made building tech companies in America look irrational on a spreadsheet.A bipartisan group of lawmakers is pushing to repeal the Section 174 change, with business groups, CFOs, crypto executives, and venture capitalists lobbying hard for retroactive relief. But the politics are messy. Fixing 174 would mean handing a tax break to the same companies many voters in both parties see as symbols of corporate excess. Any repeal would also come too late for the hundreds of thousands of workers already laid off.And of course, the losses don’t stop at Meta’s or Google’s campus gates. They ripple out. When high-paid tech workers disappear, so do the lunch orders. The house tours. The contract gigs. The spending habits that sustain entire urban economies and thousands of other jobs. Sandwich artists. Rideshare drivers. Realtors. Personal trainers. House cleaners. In tech-heavy cities, the fallout runs deep — and it’s still unfolding.AdvertisementWashington is now poised to pass a second Trump tax bill — one packed with more obscure provisions, more delayed impacts, more quiet redistribution. And it comes as analysts are only just beginning to understand the real-world effects of the last round.The Section 174 change “significantly increased the tax burden on companies investing in innovation, potentially stifling economic growth and reducing the United States’ competitiveness on the global stage,” according to the tax consulting firm KBKG. Whether the U.S. will reverse course — or simply adapt to a new normal — remains to be seen.

Insights Harvard Business Publishing Unveils Harvard Business Impact as New Brand for Corporate Learning and Education Units Rebrand affirms the company’s bold vision to develop leaders through transformative learning. Boston, MA – June 4, 2025 – Harvard Business Publishing (HBP) announced today the launch of Harvard Business Impact, a new brand identity for its Corporate Learning and Education market units. This new identity reflects a shared purpose: to shape the future of leadership by empowering individuals, teams, and organizations with transformative, research-based learning experiences. It also reinforces HBP’s mission to deliver measurable, lasting impact across both global enterprises and educational institutions—by developing leaders who can navigate complexity and drive progress. The new brand and logo signal a bold, modern approach to leadership development while maintaining the academic rigor and quality that are hallmarks of the Harvard name. The unified brand creates a cohesive voice in the market, amplifying HBP’s ability to meet the evolving needs of leaders and learners worldwide. “Harvard Business Impact communicates our belief that lasting leadership is built through continuous, applied learning,” said Sarah McConville, Co-President of Harvard Business Publishing. “Under this new identity, we are bringing the full power of our insights, partnerships, and learning expertise to move leaders forward at every stage.” With a presence in over 75 countries, Harvard Business Impact serves more than 300 enterprise clients and over 4,000 educational institutions. Its two dedicated units—Enterprise and Education—deliver transformative learning experiences that span the full leadership journey, from students in the classroom to executives in the boardroom. The Education unit at Harvard Business Impact empowers academic institutions to deliver active learning experiences that prepare students for the complex challenges of their future work. With over 65,000 learning materials—including case studies, simulations, articles, and online courses—paired with expert teaching guidance, the group equips educators to shape the next generation of global business leaders and thinkers. The Enterprise unit at Harvard Business Impact partners with global organizations to design and deliver leadership development programs that drive transformation at scale. Solutions are designed to build leadership capabilities across the enterprise—from emerging leaders to senior executives—through immersive, scalable, and contextualized learning experiences. Harvard Business Publishing continues as the parent organization, encompassing both Harvard Business Impact and Harvard Business Review. Harvard Business Review remains the leading destination for smart management thinking. Together, they provide a unified platform for leadership development and insight. About Harvard Business ImpactHarvard Business Impact builds leadership capabilities across organizations and institutions worldwide. Through research-based insights, real-world relevance, and a commitment to continuous growth, the brand empowers individuals and teams to navigate complexity, drive transformation, and lead with confidence. Harvard Business Impact is part of Harvard Business Publishing, an affiliate of Harvard Business School. About Harvard Business PublishingHarvard Business Publishing was founded in 1994 as a not-for-profit, independent corporation that is an affiliate of Harvard Business School. Its mission is to empower leaders with breakthrough ideas that solve problems, that elevate performance, and that unlock the leader in everyone. Through its articles, books, case studies, videos, learning programs, and digital tools, HBP reaches thousands of organizations and millions of subscribers and social media followers worldwide. Share this resource Share on LinkedIn Share on Facebook Share on X Share on WhatsApp Email this Page Connect with us Change isn’t easy, but we can help. Together we’ll create informed and inspired leaders ready to shape the future of your business. Contact us Latest Insights Strategic Alignment Harvard Business Publishing Unveils Harvard Business Impact as New Brand for Corporate Learning and Education Units Harvard Business Publishing announced the launch of Harvard Business Impact, a new brand identity for… Read more: Harvard Business Publishing Unveils Harvard Business Impact as New Brand for Corporate Learning and Education Units News Digital Intelligence Succeeding in the Digital Age: Why AI-First Leadership Is Essential While AI makes powerful operational efficiencies possible, it cannot yet replace the creativity, adaptability, and… Read more: Succeeding in the Digital Age: Why AI-First Leadership Is Essential Perspectives Digital Intelligence 4 Keys to AI-First Leadership: The New Imperative for Digital Transformation AI has become a defining force in reshaping industries and determining competitive advantage. To support… Read more: 4 Keys to AI-First Leadership: The New Imperative for Digital Transformation Infographic Talent Management Leadership Fitness Behavioral Assessment In our study, “Leadership Fitness: Developing the Capacity to See and Lead Differently Amid Complexity,”… Read more: Leadership Fitness Behavioral Assessment Job Aid The post Harvard Business Publishing Unveils Harvard Business Impact as New Brand for Corporate Learning and Education Units appeared first on Harvard Business Impact.

Titans of industry cannot come to terms. Despite the literal gap between them being a matter of feet—maybe 30 or so by my count—when their two locomotives come to a standstill in a tunnel with miles of track in either direction, Zsa-zsa Korda (Benicio del Toro, tyrannical, avuncular) is unable to bridge the final inches with Leland and Reagan (Tom Hanks and Bryan Cranston, stone-faced). It’s an odd situation that becomes odder still when all parties realize the fate of their multimillion-dollar venture must now come down to a game of chance: and this one a bet on whether a Middle Eastern prince (Riz Ahmed) can sink a granny shot from below his knees while playing basketball’s ugly, redheaded step-cousin, HORSE.  It was at this exact moment I realized Wes Anderson had returned to full, magnificently daffy form. As easily the prodigal Texan’s best film in over a decade, The Phoenician Scheme rekindles much of the mirth that informed so many of Anderson’s early films. It is also the first instance one has had any narrative propulsion or tension since his last masterpiece, The Grand Budapest Hotel. While I would hesitate to place such lofty titles onto Phoenician, rest assured that it’s a balmy good time at the cinema where longtime fans get to again spend an evening with impeccably dressed cheats, droll scoundrels, and other variants on the unseemly father figure. Take del Toro’s Korda for instance. He begins the film by surviving what is jointly his sixth plane crash and assassination attempt. (The industrialist’s pilots fare less happily from his habit of falling out of the sky.) He isn’t sure who wants to kill him, but he seems confident it’s probably justified. Of his nine children, eight prepubescent boys live at home with him where their resentments already border on the homicidal. And the other offspring, a daughter he never really knew, wants nothing to do with him, even after he promises to bequeath her his entire fortune “on a trial basis.” Indeed, despite being a novitiate nun, Liesl (Mia Threapleton) has a tough time with forgiveness, especially when it comes to a would-be patriarch or patron. She does agree to at least get to know the old man, though, after he decides to gallivant around the world in a bid to save his empire (hence the aforementioned HORSE of fate). Rather boldly they even board plane after plane, alongside Korda’s ineffectual Swedish nanny-turned-attendant, Bjorn (a chipper Michael Cera doing an accent about three clicks south of the Muppets’ Chef). Together they meet a starry ensemble of walk-on cameos and eccentric business partners, my favorite of which is a preternaturally giddy Jeffrey Wright. Yet always operating beneath the surface is another tale of resentments between bad parents and their adult children. That plus a kooky murder mystery where Zsa-Zsa somehow keeps avoiding being the dead body. From the name of the protagonist alone, Anderson seems intent to signal to audiences with any degree of film knowledge that he is playing once more in the sandbox of his influences. It is hard to imagine a cineaste like Anderson, for example, hearing the moniker “Korda” and not thinking of anti-fascist Hungarian refugee-turned-British filmmaker, Alexander Korda, who directed aesthetic classics like The Thief of Baghdad (1940) and That Hamilton Woman (1941). Furthermore, Anderson pulls just as much from Korda contemporaries like fellow Hungarian ex-pat Michael Curtiz, particularly when Korda and Lisel wind up at a nightclub owned by Marseille Bob (Mathieu Amalric). And yes, another movie about traveling nannies and a precocious Liesl is alluded to as well. But the reason The Phoenician Scheme works so much better than Anderson’s last several movies is that while the filmmaker is visibly delighting in his references and what are almost assuredly private jokes between himself and co-writer Roman Coppola, the director also is avoiding the trap of becoming distracted by the aesthetics. Phoenician is still a beautifully designed world of straight lines and adroit square compositions, courtesy of cinematographer Bruno Delbonnel, where nothing feels natural. Not even the sun or tree vines discovered after Korda, Liesl, and Bjorn become lost in a jungle have any reality about them. But the simple pleasure of observing visual confections is not the be-all end unto itself that it previously was. The travelogue nature of the plot, in which a father and daughter go on an odyssey of unconventional boardroom meetings that include assassins, freedom fighters, and organized crime bigwigs, provides a skeletal structure where Anderson can graft on his increasing preference for narrative vignettes, but there is an emotional spine as well between Korda and Liesl that makes both the jokes and the pathos ebullient. Del Toro has never seemed bigger or more unshackled than as Zsa-zsa. Like most Anderson protagonists, Korda rarely speaks above a polite monotone, but his double-breasted confidence and adventurism provides del Toro with a refreshingly uninhibited floorspace. It also pairs nicely when bantering with Threapleton, a real discovery of a young talent who plays a nun with conviction, even as the twinge of curling judgment on her smile suggests she may never see Heaven. But then she dryly must channel the patience of Job when dodging the advances of a tipsy Bjorn (again, Cera is having too much fun) and the would-be buy-offs of an absentee father. The terrain of an unhappy adult and their aging parent is terrain Anderson has walked many times, but there’s a renewed vigor in his step in The Phoenician Scheme, perhaps because it is the first time he has crossed this territory where he is closer in age to the latter than the former. There is empathy for all parties, though, and new tricks to his whimsy, such as his elegant compositions repeatedly being shattered in close-ups where the camera is assaulted by various subjects filled with so much rage that they literally assail the fourth wall. The Phoenician Scheme is simply a lovely work from an artist with a fresh spring in his step. If you already count yourself among his admirers, it’s a return to form with moments of divine inspiration (just wait until you see who he cast as God). For the rest, it may not cause conversion, but it’s certainly worth sharing some communion wine over. The Phoenician Scheme premiered at the Cannes Film Festival on May 18. It opens in limited release on May 30 and wide on June 6. Join our mailing list Get the best of Den of Geek delivered right to your inbox!

Enterprises today face a critical imperative. Artificial intelligence is not just a technological evolution; it is a strategic driver of business transformation. AI is reshaping competitive advantage, redefining business models, and unlocking new revenue streams. Yet, many organizations continue to treat AI as a technical add-on, rather than a core business capability. According to a 2023 McKinsey report, organizations that integrate AI across their operations are 1.5 times more likely to experience double-digit revenue growth.  For CIOs and enterprise architects, AI is no longer an IT issue -- it’s a boardroom priority. AI’s role extends far beyond driving efficiencies in operational processes. It is the key to unlocking agility, reshaping decision-making, and transforming business models. CIOs must lead the charge in embedding AI as a strategic enabler, aligning technology with the enterprise’s broader objectives to drive sustainable growth. The Strategic Impact of AI: Drive Business Outcomes Many companies are on the verge of digital transformation to modernize their IT landscapes, yet AI is often viewed as a mere innovation metric, added to enhance existing systems. AI should be embedded when designing core business processes to align business architecture with IT architecture. Related:AI’s true potential lies in its ability to drive enterprise-wide agility, transform decision-making, and accelerate business outcomes. AI empowers leadership teams by providing real-time, data-driven insights that enable smarter, faster decisions. CIOs and enterprise architects must work together to ensure that AI adoption is seamless and strategically integrated, avoiding the temptation of tactical, short-term solutions that fail to scale.  The CIO Playbook: Leading AI-Driven Transformation To harness AI’s full potential, CIOs need a structured roadmap for its integration into the business. Here’s a playbook for AI-first enterprise transformation: Establish a clear AI vision aligned with business goals.  AI should not be siloed within the IT department; it must be part of a broader strategic vision. CIOs should collaborate closely with the C-suite to align AI initiatives with the organization’s core objectives-whether that’s driving customer engagement, enhancing operational efficiency, or unlocking new revenue streams. Invest in enterprise-wide AI integration.  AI must be embedded across all facets of the organization: business, technology, data and applications. This requires a holistic approach to AI architecture, integrating AI at all levels to ensure scalability and flexibility as the business evolves. Related:Leadership Imperative: Govern AI for Long-Term Success As AI continues to evolve, CIOs must play a critical role in shaping AI governance to ensure long-term business success. This includes managing risk, ensuring ethical use, and embedding AI into the enterprise’s culture. For CIOs, AI governance is more than compliance; it’s about creating a framework that promotes innovation while safeguarding the organization’s values and business priorities. The Road Ahead For CIOs and enterprise architects, the question is no longer if they should adopt AI, but how to embed it at the heart of enterprise transformation. AI-first organizations -- those that embrace AI as a core driver of business change -- are outpacing competitors in digital transformation maturity.  AI has the power to redefine leadership decision-making, enhance operational performance, and fuel new business models. But to reap the full benefits, CIOs must lead with vision, govern strategically, and integrate AI seamlessly into the organization’s DNA. Those who do will position their enterprises for long-term, sustainable growth.