Designing Work That Works: How AI, Agents, and Data Are Rehumanizing the Enterprise

For decades, organizations have been using technology to make workers faster, more efficient, and more compliant. But what if that’s been the wrong goal entirely? What if we’ve been building faster horses when we should have been building self-driving cars?

That provocation set the tone for one of Innovation Summit 2026’s most energetic and wide-ranging sessions. Marcus Mossberger, a workforce intelligence strategist and self-described recovering HR practitioner, made a bold and well-supported case: the more organizations genuinely embrace AI, the more human work will become. Not less human. More.

The session covered workforce shortages, the death of the traditional job, the four-day work week, portfolio careers, the psychology of what people actually want from work, and why the role of management is about to change beyond recognition. It was part keynote, part open conversation—and the ideas it surfaced are directly relevant to any organization trying to figure out not just how to deploy AI, but how to design the work environment that surrounds it. Here are the key takeaways.

About the Session

Marcus Mossberger is the Chief Market Strategy Officer at LYTIQS, a platform that sits on top of core HR and ERP systems to help organizations make better decisions about and for their people. His background spans HR practice, organizational psychology, and workforce technology—giving him a perspective that connects the behavioral science of what motivates people at work with the practical realities of how organizations structure, deploy, and develop talent. His session at Innovation Summit 2026 was a solo keynote with extensive audience participation, drawing on research from Deloitte, Martin Seligman’s positive psychology framework, and his own field experience advising CHROs and people leaders.

Stop Making Drivers Better. Build the Self-Driving Car.

The framing that anchored the entire session came from a Tesla ride to the airport: Mossberger’s driver hit a button, never touched the wheel for 45 minutes, and spent the whole trip talking about his plan to buy three more cars and let them earn $35,000 apiece while he sits at home. The punchline landed hard—and so did the analogy it unlocked.

For a long time, Mossberger argued, organizations have been applying technology to make workers better at the jobs they already have. More dashboards, more training, more bells and whistles on the existing process. That’s the equivalent of adding features to a car to make the driver more capable. But the breakthrough, as Tesla demonstrated, comes from asking a fundamentally different question: what if we just didn’t need a driver?

Applied to work, the question becomes: which tasks in your organization shouldn’t require a human at all—and what does that free the human to do? His core thesis is that AI, applied with that question in mind rather than the optimization question, will make work more human—not by eliminating humans, but by stripping out the administrative, transactional, and compliance-driven work that most people find least meaningful, and returning human energy to the work that most people find most meaningful.

“The more that we embrace technology, the more we embrace AI, the more human work will become. If we can take the administrative, transactional, manual things that most people don’t want to do, it’s going to have a positive impact.” — Marcus Mossberger, Chief Market Strategy Officer, LYTIQS

This isn’t wishful thinking—it’s a design directive. The organizations that will get the most from AI aren’t the ones asking “how do we automate this task?” They’re the ones asking “if this task were automated, what would we want our people doing with the time?”

That second question is harder, more strategic, and ultimately more valuable. For HIKE2’s clients, it’s the question that connects AI deployment to workforce design—and it’s the one too many implementations skip.

Calculate Your AI Exposure Rate—Before Someone Else Does It for You

One of the session’s most actionable challenges was a show of hands: how many people in the room had calculated the AI exposure rate of any job in their organization? Not a single hand went up.

Mossberger’s point was sharp: if you haven’t mapped which tasks within each role are candidates for AI automation, you’re making workforce decisions without the most important variable in the equation. And the stakes are significant. His illustration—a retail worker’s eight core tasks, at least four of which could be automated today—showed how quickly the exercise reveals both opportunity and risk hiding in plain sight inside every job description.

The same analysis applied to management roles was even more provocative. Break management down to its core functions—operational oversight, compliance and safety, resource management, decision making, coaching and performance—and at least half, arguably more, is already automatable by existing technology. Not the coaching. Not the human judgment calls. But the clock-in monitoring, policy adherence tracking, schedule management, and reporting? Those are already within reach of current AI and automation capabilities.

The implication isn’t that managers will disappear. It’s that the role of management is being fundamentally redesigned—away from compliance and control toward the things that actually require human presence: coaching, relationship-building, creative problem-solving, and the judgment calls that technology surfaces but shouldn’t make alone. Organizations that redesign management proactively, with AI exposure analysis as the starting point, will be far ahead of those that wait for the disruption to force their hand.

For any organization doing workforce planning, talent strategy, or role redesign in the context of AI adoption, this analysis is table stakes. HIKE2’s advisory practice helps clients work through exactly this kind of capability mapping—connecting AI deployment strategy to the human roles that surround it.

The End of Jobs (As We Know Them), and the Rise of Skills

Mossberger drew on Deloitte’s Human Capital Trends report to make an argument that challenged one of the most basic assumptions in workforce management: the idea of the job itself. Deloitte’s framing is blunt—not that jobs are disappearing, but that organizing talent around fixed job descriptions is becoming an obsolete practice in a world where the half-life of a skill has collapsed from roughly a decade to less than two years.

The practical implication: hiring someone “for a job” when that job will look fundamentally different within 18 months means the job description was wrong before the ink dried on the offer letter. What organizations need instead is a skills-based approach—understanding what transferable capabilities a person brings, and building the organizational flexibility to deploy those capabilities across a wider range of activities as needs evolve.

He illustrated this with a real example from the audience: a developer hired as a Salesforce admin who, when people started leaving the organization, was given the latitude to touch anything that moved—and ended up spanning multiple platforms, putting out fires, and operating well above his original scope. That’s not a workforce anomaly. That’s a model. Organizations that explicitly design for that kind of internal mobility—formally, programmatically, not just by accident—build resilience into their talent base that no hiring strategy can replicate.

“We pigeonhole people and say, ‘You are this and therefore that’s all I expect from you.’ We have to stop doing that. When you look at the labor shortages that are coming, the new expectations of the next generation—you have to start thinking differently about how you structure your organizations, or you will get left behind.” — Marcus Mossberger, Chief Market Strategy Officer, LYTIQS

The four levers Deloitte identifies for talent—build (develop existing people), buy (recruit externally), borrow (contract and contingent), and bot (agents)—are evolving into a more sophisticated set of multipliers: blending humans and machines, unlocking human potential by boosting capability, bridging people to work that aligns with their skills and goals, and breaking away from traditional work structures entirely. Organizations that only pull the first two levers will find themselves increasingly unable to compete for talent or capability against those using all four.

What People Actually Want from Work: PERMA + Agency

Mossberger’s most personal section drew on his postgraduate work in the psychology of kindness and wellbeing at the University of Sussex and the foundational positive psychology framework of Martin Seligman: PERMA. Positive emotion, Engagement, Relationships, Meaning, and Achievement. Each element, he argued, represents something that AI can help organizations deliver more of—not less.

Positive emotion comes from removing the friction and frustration of work that feels pointless. Engagement—the state of deep flow where three hours disappear without noticing—is more accessible when tedious administrative overhead isn’t constantly pulling people out of the work they’re best at. Relationships, which Mossberger noted have become both more important and more explicit since the pandemic blurred the line between professional and personal, are enriched when people have the time and energy to invest in them. Meaning is amplified when work is redesigned around purpose rather than compliance. And achievement—the desire to be genuinely good at something—is easier to attain when the right tools are available and work is matched to individual strengths.

To PERMA, Mossberger added his own sixth element: Agency. The ability to choose when, where, and how you work.

He made the case that agency is particularly critical for the next generation of workers—and that organizations willing to design for it, rather than grudgingly accommodate it, will have a significant talent advantage. This isn’t soft idealism. It’s backed by research showing that productivity in four-day work week pilots either holds steady or improves, that remote and asynchronous work arrangements can produce exceptional outcomes when tied to clear deliverables, and that the organizations treating workers as capable adults—measuring outcomes rather than hours—are seeing both higher performance and lower turnover.

The practical challenge is that most organizational structures were designed for the industrial era—built around time, location, and compliance rather than outcomes, autonomy, and purpose. Redesigning those structures to align with what people actually want from work, while maintaining the accountability and coordination that organizations need, is the leadership and design challenge that AI makes both more urgent and more possible to solve.

The Timeless Skills AI Can’t Replace—and Can’t Afford to Erode

The session closed with a framework Mossberger called the Timely and the Timeless. The timely is AI—the tools, the capabilities, the relentless pace of change. The timeless is the set of human capabilities that don’t decay with the tools: communication, emotional intelligence, critical thinking, problem-solving, creativity, authenticity, and above all, humility.

On humility specifically, he cited a striking finding from his time at a behavioral assessment company that had evaluated 200 million people across 26 characteristics: the single best predictor of high performance was humility. Not confidence. Not technical skill. Humility—the disposition to say “I don’t know it all, I have a lot to learn, I’m curious.” That is, in other words, the orientation that makes someone capable of learning at the pace AI is requiring everyone to learn.

The urgency here is real. With 70% of today’s workforce skills expected to change significantly by 2030—per the Microsoft Copilot team’s own forecast—and the half-life of any given skill now under two years, the capacity to continuously re-skill, up-skill, and cross-skill isn’t a nice-to-have. It’s the fundamental workforce capability that everything else depends on. Organizations that invest in building this capability—through internal mobility programs, internal side hustle structures, learning-embedded work design, and the psychological safety to try things and fail—will have a workforce that can adapt. Those that don’t will face an increasingly brittle talent base, no matter how good their AI tools are.

The session’s final provocation was a question about the structure of careers themselves: if we’re going to live to 100, does it make sense for education to happen only at the beginning, work to happen only in the middle, and retirement to happen only at the end? Or is the future one of repeated cycles—multiple stages of learning, working, resting, and returning—that look nothing like the linear careers most organizations were designed to support? Mossberger’s answer was that the organizations willing to ask that question now, and start designing for it, will be the ones that attract and retain the talent they need for whatever comes next.

Watch the Full Session

Marcus Mossberger’s full presentation includes a deeper dive into portfolio careers and self-sovereign career data, a live audience discussion on the four-day work week and what people would actually do with an extra day, the complete PERMA framework with audience additions, and a thought-provoking exchange on how these ideas apply to frontline and essential workers—not just knowledge workers.

Ready to Design Work That Actually Works?

The organizations that will lead in the AI era aren’t just the ones deploying the best tools. They’re the ones that designed the work around the tools—understanding which tasks to automate, which roles to redesign, which skills to build, and how to create the conditions where people can do their best work alongside intelligent systems.

HIKE2 helps organizations connect AI strategy to workforce design—mapping AI exposure across roles, redesigning workflows around human strengths, and building the change management infrastructure that makes transformation sustainable. If you’re ready to move from faster horses to self-driving cars, let’s talk.

Contact HIKE2 to start the conversation →