• Maybe a useful way to think about what it would be like to coexist in a world that includes intelligences that aren’t human is to consider the fact that we’ve been doing exactly that for long as we’ve existed,
• One is how much we matter to them.
• A second axis is to what degree these animals have a theory of the human mind. How much do they know about what is going on in our minds?
• The third axis is how dangerous they are. What kind of agency does the animal have to inflict harm on human beings?
• What people worry about is that we’ll somehow end up with AIs that can hurt us, perhaps inadvertently like horses, or deliberately like bears, or without even knowing we exist, like hornets driven by pheromones into a stinging frenzy.
• Not out of malicious intent per se but just from a general belief that everything should have to compete, and that competition within a diverse ecosystem produces a healthier result in the long run than raising a potential superpredator in a hermetically sealed petri dish where its every need is catered to.
• Marshall McLuhan wrote that every augmentation is also an amputation.
• We may end up with at least one generation of people who are like the Eloi in H.G. Wells’s The Time Machine, in that they are mental weaklings utterly dependent on technologies that they don’t understand and that they could never rebuild from scratch were they to break down. Earlier I spoke somewhat derisively of lapdogs. We might ask ourselves who is really the lapdog in a world full of powerful AIs.
• To me this seems like a downside of AI that is easy to understand, easy to measure, with immediate effects, that could be counteracted tomorrow through simple interventions such as requiring students to take examinations in supervised classrooms, writing answers out by hand on blank paper.
• And when the competition is in the realm of intelligence, that means preserving and advancing our own intelligence by holding at arms length seductive augmentations in order to avoid suffering the amputations that are their price.

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• While analysis linking tech spend to labor productivity is notoriously inexact, labor productivity has grown by close to 2 percent over the same period of time
• Data further show that the relationship between IT spend levels and labor productivity varies by sector, creating more uncertainty.
• These trends help illustrate at a macro level why executives are often skeptical about requests for more IT investments within their businesses.
• Technology is a deciding factor in a company’s ability to compete and, when the strategy and execution are strong, deliver outsize returns. Our analysis suggests that enterprises with high-performing IT organizations have up to 35 percent higher revenue growth and 10 percent higher profit margins than their peers
• Bridging the gap between what tech is capable of and how it often falls short requires a much better understanding of the underlying value of tech
• While the quest for better ROI and more accountability on tech spend is a long-standing issue, new innovations and models have profoundly shifted technology spend dynamics
• ome 79 percent of IT spend now goes to operating expenditures.⁵2025 CIO Agenda, Gartner, October 2024. This shift, along with the growing use of tokens through large language model (LLM) services, is giving businesses a much clearer understanding of spend at the unit cost level and spurring the growth of financial operations (FinOps) to better manage spend
• The integration of gen AI into software, for example, is pushing up usage costs (such as cost per prompt), while the promise of gen AI agents is already causing CIOs and chief human resources officers (CHROs) to rethink their talent strategies and spend models (including training and career pathing).
• Cyber and compliance necessities. The tech costs of doing business in the modern world—that is, operating reliably and responsibly—have increased significantly
• Incentives reward tech delivery over business-wide value. The business leaders who pay for IT to develop a product or service are often not accountable for the true costs of developing and maintaining that product or service.
• Tech debt. A focus on point solutions and a lack of clarity on the resulting complexity lead to ever greater cycles of tech debt—essentially the “tax” a company pays to redress technology issues when undertaking new development. Companies pay an additional 10 to 20 percent to address tech debt on top of the costs of any project, creating a significant drag on productivity.¹¹
• Productivity gains go to a variety of stakeholders but not the business. A range of IT programs result in benefits that accrue to others outside of the business. Some 10 to 20 percent of productivity resulting from work-from-home investments benefits employees rather than the enterprise (such as improved working conditions and freed-up time for personal activities). McKinsey analysis further suggests that 5 to 10 percent of IT productivity improvements can be lost to vendors (for example, cloud service providers that are no longer passing on the reduction in hardware costs to their customers).
• Moving the technology estate to a metered consumption model can allow companies to track and attribute any tech used at a unit cost level. This transparency helps companies hold teams accountable for total costs and the tech debt they generate, while developing incentives to minimize it.
• Making this shift requires building all technology services and capabilities as consumable products. This means establishing standardized APIs to provide people and systems with an easy way to consume each product
• Every technology product should have a balance sheet that provides true measurement of the tech debt and indirect costs.
• Creating transparency requires leaders to automate processes and manage tech through continuous integration/continuous delivery (CI/CD).
• Over the past five to seven years, IT has been moving to a product operating model. But this shift has largely failed to extend to the rest of the business,

• The shift companies will need to make is to manage all technology initiatives as products run by cross-functional teams. These teams, led by the business, operate with the autonomy, accountability, and incentives to deliver. Our analysis shows that top companies in product operating model maturity have 60 percent greater total shareholder returns than companies in the bottom half and a 16 percent higher operating margin.¹³Aditi Chawla, Martin Harrysson, Hannah Mayer, and Megha Sinha, “The bottom-line benefit of the product operating model,” McKinsey, December 19, 2023.

   
• The most critical role in this product model is the product manager (PM), who is essentially empowered to run the product like a business.
• Any effective PM should be able to identify and address both the hard and soft costs that counteract productivity, such as the size of the demand, whether outcomes actually deliver value to the business, and what dependencies are required for the product to capture its full value, as well as track KPIs closely
• decision-making process from traditional heuristic models to more analytically driven ones. In this way, companies can reduce the “pilot purgatory” of subscale programs and focus on initiatives that can generate meaningful value for the business.
• A good starting point is focusing tech investment on domains (that is, an end-to-end process or journey) rather than individual use cases.
• Within a domain, tech leaders need analytical rigor in sizing the value potential of each use case on their road map. When it comes to using gen AI, for example, McKinsey’s latest AI survey shows that, out of 25 attributes tested, the redesign of workflows has the biggest effect on an organization’s ability to see EBIT impact.
• The increasing adoption of agentic AI across different parts of IT is opening the door to revolutionary changes in how companies run their technology estates. Early programs show a 40 to 50 percent acceleration in tech modernization timelines and a 40 percent reduction in costs derived from technology debt
• Traditional talent strategies and team configurations will fundamentally change (some roles are likely to absorb new responsibilities), which will result in a complete rethink of enterprise tech resourcing models

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• Enterprise AI agents are moving beyond simple chatbots as interfaces to information and automation, and will mostly work in the background and with each other, rather than competing for human attention.
• this shift will shake up enterprise software and we can expect several players to battle it out in the hope of owning the role of ‘agent orchestrator’ in the enterprise. But in fact, as Deutsche Bank analysts recently suggested, Microsoft may be the goldilocks option here for many firms, given its commitment to agentic AI in the workplace.

• The issue lies in what companies are getting for that spend, and the track record on that score is mixed.

  While analysis linking tech spend to labor productivity is notoriously inexact, labor productivity has grown by close to 2 percent over the same period of time
• leading companies will do more of their own development, and with agentic AI they can adapt, augment and automate systems to their own specific requirements

• As their systems and processes become more programmable as a result, the rest of the business will also start to move in the same direction.
• We have seen the amusing failures of Duolingo, the less amusing failures of fictitious legal analyses that can cause real world harms, and the rather predictable back-pedalling of AI cheerleaders like Klarna, who tried to replace humans in the loop for too quickly.
• In the United States, DOGE’s recklessness in grabbing sensitive data and running it through untested AI tools has probably created such wide open backdoors for hostile state actors that the real level of penetration may be too much to admit
• We need smarter approaches to security, and also to AI governance.
• Marshall McLuhan wrote that every augmentation is also an amputation.
• Today, quite suddenly, billions of people have access to AI systems that provide augmentations, and inflict amputations, far more substantial than anything
• We may end up with at least one generation of people who are like the Eloi in H.G. Wells’s The Time Machine, in that they are mental weaklings utterly dependent on technologies that they don’t understand and that they could never rebuild from scratch were they to break down
• now that software development can be invoked by natural language - and so potentially anybody can do it - we can start to focus on the many, important human skills and forms of critical thinking that will be helpful in navigating this shift without losing our humanity.

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• although creating “productive and engaging workplaces” is a business priority, less than half had confidence that their current digital environment was able to support this.
• 89% understand that to achieve these benefits, businesses need to embrace more than just new tools. 

• he seven key barriers blocking workplace transformation:

   
   
  1. Lack of vision as to how digital workplace transformation can support strategic goals
   
  2. Other IT initiatives take precedence 
   
  3. Lack of understanding
   
  4. Insufficient time
   
  5. Difficulty building a business case
   
  6. Lack of buy-in from senior leaders
   
  7. Insufficient IT budget

• Yet 44% of IT leaders explained that not understanding how to digitally transform their organization is one of their top three challenges.

   

• “True transformation isn’t just about adopting AI tools. It’s about reimagining the entire workplace,” he tells UNLEASH. 

   
• a comprehensive approach to tackle intersectional challenges, HR leaders should therefore plan to overcome common the most common obstacles; change management, skills gaps, tech integration complexities, and cross-functional alignment to improve the transformation process.
• three simple steps to execution: holistic thinking, optimizing spend, and accepting expert guidance. 
• developing a “comprehensive roadmap” to address these four key challenges
• partnering with other organizations that have already achieved a successful transformation,
• “You can give an employee the best tool to improve their workplace experience, but if they aren’t educated on how to use it, there will be slow adoption and you won’t see the business benefits.”

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• With the ongoing focus on hybrid work and digital transformation (powered by GenAI), leading organizations are exploring novel ways to structure and brand their executive roles. Moderna recently ​combined​ its HR and IT departments under one leader: Tracey Franklin, the Chief People and Digital Technology Officer.

• I’m only using Moderna as a springboard for something bigger.
• the journey towards a more unified "Chief of Work" has evolved over the years.
• Moderna isn't the only firm with interesting C-suite roles. For example, ​Jacqui Canney​ is Chief People and AI Enablement Officer at ServiceNow, and ​Sharon Doherty​ is Chief People and Places Officer at Lloyds.

• I got blank stares when I asked how they integrated people and spatial experience data.

  The silos remained, just under a different reporting structure.
• eal estate organizations can sit almost anywhere in the organization. They're usually in Finance but could be in HR, COO/CAO, IT, and even Legal.
• the Head of Technology Infrastructure also took on Corporate Real Estate.
• That change dramatically accelerated the adoption of innovative technologies,
• The walls between spaces and systems came down, not because of a fancy new title, but because one leader could see and make integrated decisions across both domains.
• "To optimize performance and the experience of work, the real estate, technology, and people and talent functions need to be aligned to a common purpose under the COO or even perhaps a Chief of Work."
• "Human Resources as 'guardians of culture' are seen as important but often fail to step up and can be at times barriers. Shared Services and Corporate Real Estate are key implementers but create only workplace experiences, not work experiences."
• • Strategic architecture matters more than reporting lines. The EX organization must function as a visionary product owner with a coherent view of how work happens, regardless of its position.
  • Cross-functional accountability trumps hierarchy. End-to-end responsibility requires dedicated teams and visible executive ownership, not only consolidated titles.
  • Single source of truth. As I wrote for ​Vibe Officing​, companies must monitor both physical and digital experience metrics.
  • Dedicated, deployable funding. To address mismatched incentives for ​EX costs​, create dedicated budgets for use across all functions.
• • Dedicated Function: A direct CEO report with enterprise-wide authority (closest to "Chief of Work"). This approach maximizes visibility but could well struggle with execution authority.
  • Embedded within HR / Talent: The EX function reports to the CHRO but includes strategic elements of technology and physical space. This is the most common approach in my experience, especially with more real estate teams reporting through HR.
  • Virtual/Distributed Model: EX strategists from HR, IT, Real Estate, and other disciplines maintain their reporting lines but collaborate in an agile "chapter" model. This preserves depth of expertise while enabling cross-functional coordination.
• EX isn't an easy fit for a traditional matrix organization. It shouldn't sit with a function, it shouldn't sit with a BU or product. EX has to sit with the part of the matrix that balances it all agnostically, which is general management or the Office of the CEO. But often they don't want it, or don’t know how to do it, or both. So that’s our problem."
• Moderna's merger of People and Digital Technology reflects a practical truth: the employee digital experience is inseparable from the general employee experience.
• But we don't want HR running cybersecurity, or IT running the promotion cycle, or real estate rolling out Microsoft CoPilot. The opportunity lies in creating strategic alignment at the leadership level while maintaining operational excellence within domains.

• This is why the ideal "Chief of Work" function would include strategists from each discipline:

  • From real estate: workplace strategists and design researchers
  • From HR: people analytics, employee listening/engagement
  • From IT: end user collaboration strategy and UX researchers

• But organizations shouldn't fixate on perfect structures, they should:

  1. Create a clear ​”North Star” vision​ that connects EX across domains
  2. Establish common metrics that transcend functional boundaries
  3. Build cross-functional teams that collaborate despite reporting lines
  4. Create spaces where HR, IT, and Real Estate strategists can develop shared understanding of holistic EX

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• Digital transformation should be a means to an end, but it often gets mistaken for an end in itself. This is partly why 70% of all digital transformation efforts fail — because they’re done purely for the sake of going digital without full consideration of the bigger picture.

   
• Despite the elimination of commute times, people ended up working longer hours and less efficiently than before, resulting in more excessive workloads and less work-life balance, two key drivers of workplace stress.
• But telling people to log off at 5 p.m. misses the point entirely, because it fails to address the reason for excessive workloads and rising stress — that is, how we work.
• You do not rise to the level of your goals. Your fall to the level of your systems.”
• The average person sends and receives about 121 business emails a day, spends about 23% of their time on unnecessary emails, and sends about 200 instant messages per week via platforms such as Slack.
• Bartleby’s Law posits that meetings waste 80% of the time for 80% of the people in attendance. A 2017 study led by Harvard Business School professor Leslie Perlow lends credence to this idea, with 71% of senior executives saying that meetings are unproductive and inefficient.
• To do that, we need to end the indiscriminate booking of time in our colleague’s calendars with little regard for their priorities and commitments.
• hared documents empower people to work on the same document asynchronously without bearing the burden of version control. 
• Plugins can help to effectively slow down apps like Slack, getting us out of a cycle of viewing and sharing tons of cat gifs and pop culture memes each day, moving us toward a more asynchronous use of instant messaging platforms. We can escape information overload with the Must-Read plugin, which serves up only messages that colleagues have tagged you in.
• Plugins such as BlockSite, Freedom, or Inbox Pause can block the constant influx of email for periods of the day
• As remote becomes par for the course for organizations the world over, a new wave of tools is likely to emerge. One such tool comes from the team at Automattic. They herald P2 as a platform for teams to share, discuss, and collaborate openly, without interruption. “Conversations on P2s take place in line, update in real-time, and provide space for threaded replies,”

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• IBM formally announced that 94% of typical HR questions are now answered by its AI agent, and the role of HR Business Partner is all but eliminated except for very senior leaders.
• the capabilities of AI are growing much faster than our organizations” ability to adapt, so we have to lean forward and start redesigning our companies.
• I know IBM’s story well, and I think it explains where all HR teams are going. Many years ago Diane Gherson (prior CHRO) started AI projects to automate recruitment, pay analysis, and performance management.
• she told me the AI agent helps write performance reviews, creates development plans, and coaches managers and senior leaders on a myriad of performance based decisions.
• In the case of L&D or HR business partners, I believe we could see a 20-30% or more reduction in HR headcount per employee
• While we all worry about AI taking our jobs, we have to remember that our real job is not to “do things” but to “add value” and bring complex problem solving skills to our companies.
• who explained how he and his team rationalized their job architecture from 65,000 job titles to only 600 by using new AI tools from OpenAI and Reejig
• HR professionals are going to have to train them, implement them, and “manage them” for long term success.
• move our thinking from dated concepts like “time to hire” and “course completion rates” to meaningful measures like “time to revenue” or “time to productivity” or “time to customer service excellence.”
• Stop thinking about how much money we save on headcount (which is a fleeting benefit, by the way) and focus on value creation.
• In many ways these “HR downsizing” stories are really stores of “HR crawling up the value curve,” which is really a good thing.

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