Future of Leadership and Consulting in the Age of AI: A Decade On

Ten Years Ago: A Bold Prediction

Exactly ten years ago, on July 3, 2015, we published the first version of Future of Leadership in the Age of AI. At that time, most discussions about artificial intelligence revolved around automating blue-collar jobs and routine manual tasks. Our contrarian view – based on hands-on experience implementing early AI systems in a large organization – was that AI would impact knowledge work even more profoundly. We envisioned AI evolving into super-smart pattern recognition and prediction machines, capable of augmenting or performing many cognitive tasks traditionally done by white-collar professionals. In other words, AI wouldn’t stop at the factory floor; it would move up the org chart into offices and boardrooms. This perspective was unusual then, but it has since been proven correct. In fact, as we noted, AI’s effect on the workplace “will not be limited merely to repetitive, production line-type jobs” and is “increasingly entering the realm of highly trained knowledge workers”. We even argued that managers and executives would eventually work alongside AI, and that’s exactly the world we now see around us. (And have even published a comic on this topic at Working With AI).

Looking back, we were right about the direction of change – yet even we underestimated the pace and extent of it. The past decade saw breakthroughs (like deep learning and transformer models) occur far faster than expected. As we noted in the foreword of our old book, even our own predictions about how quickly these technologies would evolve were overshadowed by the reality of today’s rapid breakthroughs. In 2015, the idea of AI writing reports, coding software, or holding fluent conversations still seemed distant. Now, in 2025, those capabilities are a daily reality. The rise of generative AI has transformed knowledge work at lightning speed. AI has leapt from theory to practice in offices everywhere, augmenting tasks from research and analysis to customer service and strategic planning. We always believed AI would reshape knowledge work – but the breadth of its impact and the speed of its uptake have exceeded even our optimistic scenarios.

Why reflect on this now? July 3, 2025, marks the ten-year anniversary of that initial publication. It’s an apt moment to take stock of how the world of work and leadership has changed in the AI era.

Back then, and for years after, we also speculated about something close to home: what these AI advancements would mean for the consulting industry (which relies on human expertise and problem-solving). We posited that consulting, being a quintessential knowledge enterprise, would not be immune to AI’s disruptions. I summarized my thoughts on that in The Future of Consulting in the Age of AI. Today, we have the benefit of hindsight – and real industry data – to see how that prediction panned out. The short answer: AI is indeed transforming consulting, arguably more than any other professional field. And as fate would have it, I now find myself as the CEO of a consulting firm called Applied Quantum (and its security-focused arm Secure Quantum), operating in this AI-transformed landscape. In other words, I’m living out the scenario we envisioned, applying those old theories in practice.

AI’s Transformation of Knowledge Work

In 2015, the mainstream view was that knowledge workers such as doctors, lawyers, analysts, consultants are relatively safe from AI, at least for a while. However, we argued that the core strength of AI is in data-driven pattern recognition, prediction, and automation of information work, which directly affects jobs centered on knowledge and decision-making. That view has become reality. Today, generative AI can draft legal contracts, diagnose medical conditions from images, generate business reports, write code, and help me write this article.

The extent of AI adoption in knowledge work is remarkable.Employees aren’t waiting for permission; many are bringing AI tools into their workflow to boost productivity. They report that AI helps them save time on drudgery, focus on more important tasks, and even be more creative. In effect, AI is functioning as a “force multiplier” for human knowledge work: automating the repetitive parts, offering data-driven insights, and allowing human experts to concentrate on complex problem-solving, interpersonal communication, and creative strategy – the areas where human judgment still outshines machines.

Equally important is the speed of this transformation. It took only a couple of years for advanced AI tools to go from novelty to nearly mainstream in many professions. The launch of user-friendly generative AI (like ChatGPT in late 2022) was a tipping point. By early 2024, usage had nearly doubled in six months and a huge share of professionals adopted it virtually overnight. Those who anticipated and embraced AI’s role in knowledge work have gained a competitive edge, while those who dismissed it as a distant threat are scrambling to catch up.

Impact on the Consulting Industry

Back when we first explored AI’s impact, we paid special attention to consulting – our own industry. Consulting has traditionally been a people-centric, knowledge-driven business: firms hire smart humans who analyze client problems and recommend solutions. The business model is often labor-intensive (think of armies of analysts working long hours) and opinion-led (built on expert judgment). We theorized that this model would face upheaval as AI systems became capable of analysis, research, and even strategic recommendations. Simply put, if AI could crunch data and generate insights faster (and perhaps more objectively) than human consultants, clients would demand new kinds of value from consulting firms.

Ten years later, this is exactly what’s happening. Consulting is emerging as one of the industries most impacted by AI – not because consultants will vanish, but because the way consulting is done is being reinvented. The Future of Consulting in the Age of AI, even though a few years old, remains very applicable. Clients now expect consulting firms to embed AI into their services for better insights and efficiency. According to a recent IBM study, 86% of consulting service buyers say they are actively looking for firms that incorporate AI and technology assets into their offerings. In fact, 66% of clients say they will stop working with consultants who don’t leverage AI in their solutions. These numbers make the trend clear: adopting AI is no longer optional for consulting firms – it’s existential. The traditional model of selling human expertise by the hour is under pressure. Clients want advisors who use cutting-edge AI tools to deliver faster, data-backed, and more certain outcomes.

Furthermore, clients, realizing that AI these days can likely do a better job than whole teams of junior analysts, are increasingly insisting on paying only for senior consultants’ time – those that can bring in experience, have managed change, have a network in the industry and competitive intelligence. And the research and number crunching and “decks” development can be offloaded to AI.

Those consulting firms that are capable of changing fast are responding by reinventing their operating models. The focus is shifting from labor-intensive processes toward AI-augmented processes. The new consulting playbook is: let AI handle the grunt work and number-crunching, while humans concentrate on empathetic consulting, creative problem-solving, and domain-specific strategy.

The consulting workforce itself is evolving. There’s a huge emphasis on reskilling and upskilling consultants to work effectively alongside AI. Global executives estimate that roughly 40% of the workforce will need reskilling due to AI and automation in just the next three years – that’s about 1.4 billion people worldwide who must learn new skills. Consulting firms are at the forefront of this effort, as they must ensure their people can build, interpret, and govern AI systems for clients. The skill set of a top consultant now spans not just business and industry knowledge, but also data science literacy and the ability to collaborate with AI in day-to-day work.

In summary, the consulting industry is transforming under AI’s influence – from how we deliver value, to what skills our people need, to what clients demand. Our prediction that consulting would have to change in the age of AI has materialized. The firms that adapt – by empowering their people with AI, redefining processes, and reinventing their service models – are poised to thrive as strategic partners to clients in an AI-driven world. Those that don’t will undoubtedly struggle to remain relevant. As someone who now leads a consulting firm, this hits especially close to home, which leads to the next section.

Leadership in the Age of AI – New Skills, New Roles

What does all this mean for leadership itself? If AI is doing more of the heavy lifting in analysis, prediction, and even decision support, how must leaders evolve? The short answer: leaders must double down on what truly makes us human, while also mastering how to harness AI for organizational success. The fundamentals of good leadership – vision, integrity, empathy, strategic thinking – remain as important as ever. But certain skills and mindsets are now absolutely critical in the age of AI:

• Technological Savvy and Adaptability: Leaders don’t need to be coders or data scientists, but they must understand AI at a strategic level. This means grasping the capabilities and limitations of AI tools, staying current on technological trends, and being willing to adapt business strategies as new AI innovations emerge. A decade ago, an executive might have delegated all the “tech stuff” to the IT department; today’s CEOs and managers, however, routinely discuss AI-driven opportunities and risks as part of core business strategy. In short, a leader in 2025 treats AI as integral to the business, not an optional add-on.
• Data-Driven Decision Making: The intuition and experience of leaders are now augmented by unprecedented amounts of data and AI-generated insights. Effective leaders leverage AI analytics to inform their decisions – whether it’s using predictive models to forecast market shifts or employing AI to gauge employee sentiment. However, they also learn to question and validate AI outputs, applying human judgment to ensure that decisions aren’t made in a blind “AI autopilot” mode. The best leaders strike a balance: they neither ignore the sophisticated analyses AI provides nor accept them uncritically. They ask the right questions, interpret results in context, and make the final call with accountability.
• Ethical and Responsible AI Stewardship: With great power comes great responsibility. AI can introduce ethical dilemmas – from bias in algorithms to privacy concerns to impacts on jobs. Modern leaders must act as ethical stewards of AI deployment. This involves setting guidelines for AI use that align with the organization’s values, ensuring transparency in how AI-driven decisions are made, and considering the broader societal impact.
• Emotional Intelligence and Human-Centric Skills: Interestingly, the more work AI handles, the more human the role of a leader becomes. Which has also been our key hypothesis from the start. Tasks like motivating teams, cultivating a positive culture, understanding customer emotions, and mentoring employees can’t be handed off to an algorithm. In fact, because AI takes over many technical or routine tasks, leaders have more bandwidth to focus on people. Empathy, communication, and interpersonal skills are thus at a premium. As we wrote years ago, those with strong social and interpersonal skills have the least to worry about from job-stealing AI. An effective leader uses AI as a tool to enhance human potential, not as a substitute for human connection.
• Continuous Learning and Innovation: Finally, leaders must foster an attitude of continuous learning – both for themselves and across their organizations. The AI field moves rapidly; what was cutting-edge two years ago can become table stakes today. Leading an organization through this means constantly exploring new ideas, experimenting with AI applications, and encouraging a culture where employees update their skills regularly. It also means being willing to drive change.

In essence, the age of AI doesn’t make human leadership obsolete – but it does redefine it. The leader’s job is shifting from managing tasks and transactions (many of which can be automated) to cultivating talent, setting a vision in a tech-driven world, and integrating AI thoughtfully into every facet of the business. Leaders also serve as role models in how to work alongside AI. If a manager openly uses AI tools to enhance her productivity, shares her learning experiences, and supports her team in doing the same, it sets a tone that AI is an opportunity, not a threat. The future of leadership, therefore, lies in embracing AI while elevating the human strengths that machines cannot replicate. And that’s more clear today then it was even when we wrote the book.

Putting Theory into Practice: My Firm’s Journey

When we wrote the original Future of Leadership in the Age of AI, it was largely theoretical and forward-looking. Now, a decade later, I have the privilege (and challenge) of applying those theories at Applied Quantum, the consulting firm I run. Those of you that know me, know that I was trying to champion the new model of consulting in my previous large consulting firms, but the changes were slow. Applied Quantum is now becoming a sort of living lab to test and refine ideas about leadership and AI adoption. Let me share how we’re navigating this transformation on the ground:

1. Embracing AI in Our Services: We have made AI a core part of our consulting offerings. Just as clients expect, we incorporate AI tools in our projects to provide deeper insights and faster results. We’re institutionalizing AI across the firm so that every engagement can benefit from it in some way. The lesson we took to heart is to not treat AI as a novelty act or one-off experiment, but to bake it into the fabric of how we deliver solutions. Most importantly, the clients can see and learn about how we use AI in every aspect of the project, and they share in the financial benefits of that use as well.
2. Reskilling and Talent Development: We identified key competencies for the AI age and are working on developing them. Combining the deep experience and expertise of our PhDs (in cybersecurity, physics, cryptography with competent and critical use of AI, will guarantee Applied Quantum’s future.
3. Rethinking Processes and Quality Control: Adopting AI also forced us to re-examine our internal processes. We asked ourselves: which tasks are better done by AI, and which by humans? How do we ensure quality and consistency when AI is involved? For client deliverables, we will use AI tools to generate a first draft of certain analyses or reports, but we always have human (senior) consultants review, refine, and add the contextual narrative. This human–AI collaboration workflow can significantly reduced project timelines, but we’ve also put in strict quality assurance steps. For instance, any AI-generated analysis gets a second set of human eyes to verify its accuracy and relevance. We treat AI as a junior analyst: incredibly fast and tireless, but needing guidance and oversight from senior humans.
4. Strategic Vision and Experimentation: As the firm’s leader, I’ve made it my mission to keep us ahead of the curve on AI innovations. This means setting a vision that we will be an AI-enabled consultancy, and constantly scanning the horizon for emerging tools or methods that could help our clients.

Through these efforts, I’m essentially testing our original theories in real life. The encouraging news is that many of the principles we believed in – embracing technology, focusing on human strengths, continuous learning, and agility – are indeed proving to be the right ingredients for success. Of course, the journey is not without challenges.

Pioneering a New Consulting Model

In addition to how we work, we’ve also taken bold steps to change our consulting business model itself in line with this new era. At Applied Quantum, we have implemented several key changes that flip the traditional consulting approach on its head:

• Outcome-Based Fees: We tie our fees to measurable impact, linking our success to the client’s success. It’s a shared-risk approach – no more endless hourly billing or watching the “ticking clock.” If we don’t deliver results, we don’t get rewarded. This model aligns incentives and assures clients that we stand behind our work.
• Inverted Pyramid: Instead of deploying large teams of junior analysts, we operate with an inverted pyramid structure. Our work is done by small teams of senior experts (physicists, cryptographers, cybersecurity pros, etc.), with AI and automation handling much of the junior-level grunt work. Clients get top-level talent directly working on their issues, not layers of hierarchy padding the bill. This lean, expert-driven model ensures higher quality, faster turnaround, and a focus on solving the problem rather than managing a big team.
• Transparent AI Assistance (Shared Benefits): We openly use advanced AI models under expert oversight and make transparency a selling point. Clients can see when and how AI is applied in our work, and they directly benefit from the efficiency and cost savings it brings. We don’t hide AI behind the scenes to quietly boost our margins; instead, we pass those benefits to the client – delivering work faster or at lower cost – which builds trust and a true sense of partnership. By sharing AI’s advantages with clients, we align our interests and reinforce that we’re in it together to achieve results.

These changes reinforce our commitment to deliver tangible value and stay ahead of the curve in the consulting industry’s AI-driven transformation. In many ways, we are putting into practice the very principles that we identified years ago and that industry analysts today predict will define the consulting firm of the future – outcome-focused, expert-driven, and openly AI-enabled.

Looking Ahead to the Next Decade

Standing at this ten-year milestone, it’s clear that the future of leadership and consulting in the age of AI we once imagined is now here – and it’s every bit as transformative as we thought, if not more so. AI has moved from the periphery of business to the very center. Knowledge work has been altered fundamentally, with intelligent machines now part of the team in almost every professional field. The consulting industry’s evolution under AI’s influence serves as a microcosm of what’s happening across the economy: adaptation, disruption, and innovation all at once. Leaders find themselves in a world where partnering with AI is a prerequisite for success, and where their role is increasingly about guiding human–machine collaboration toward positive outcomes.

What lessons can we carry into the next ten years?

1. First, embrace change early. One thing the past decade taught us is that those who adopt new technologies sooner tend to leap ahead, while laggards pay a price.
2. Second, keep a laser focus on human value-add. The question every leader and worker should continuously ask is: “What is it that we can do better than any AI, and how can AI help us do the rest?” The answer will shape how roles and organizations evolve.
3. Third, invest in learning – at both the individual and organizational level – as an ongoing process, not a one-time fix. The half-life of skills is shortening, and new competencies will be required as AI capabilities grow; a learning organization that can pivot quickly will navigate the coming waves of change more gracefully.

Finally, maintain a sense of optimism and responsibility. It’s easy to get caught between utopian hype and dystopian fear when it comes to AI. The reality likely lies in between: AI will bring incredible opportunities to enhance productivity, creativity, and prosperity, but it also introduces risks that need careful management (like bias, job displacement, or misuse). Effective leadership will be about striking that balance – innovating with optimism, while managing with prudence. As we look to 2035, we can be certain the AI tools of that time will make today’s ChatGPT look quaint. Preparing for that future starts now, by building adaptable organizations and ethical guardrails.