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Artificial Intelligence
2026 AI trends: What leaders need to know to stay competitive
Is your organization AI-ready? IMD professors and researchers predict 2026 trends in artificial intelligence. Read on and prepare to innovate – or be left behind.
If 2025 was the year that leading companies scaled their PoCs for broader digital transformation and AI adoption, in 2026, we will see organizational overhaul and a decisive victory in the battle for search dominance. Or will we? Will AI replace middle managers in the workforce? Which departments will be hardest hit?
Disruption continues; opportunity knocks
Developments in agentic AI present significant opportunities for organizations in 2026; automation, problem-solving, and decision-making drive not just efficiency but effectiveness. From transforming human resources applications to revolutionizing customer experiences, leaders who fail to capitalize on innovation will be left behind. But as they do that, and as organizations invest heavily to embed AI in their business strategies, they must also manage risk, ensure responsible governance, and build competitive advantage.
To help leaders prepare for 2026, we asked IMD experts to place their bets on what may happen in the coming year. If 2025 is anything to go by, we are sure to encounter a few surprises. But here is what we expect to see, along with advice for how to navigate through the ambiguity. Read on and consider how you, as a leader, can embed AI in your 2026 strategy for maximum impact for Q1 and beyond as you lead your organization through change.
Top AI trends for 2026
How we use it
“AI will transcend ‘tech’ talks and be seen as a facilitator for a reimagining of management.”
Mark Greeven
Professor of Management Innovation, Dean of Asia
In 2026, the most successful organizations will stop treating AI as a technology race and start treating it as a management revolution. The winners will not be those deploying the most models, but those reinventing how decisions, teams, and accountability are organized around AI.
“Executive focus shifts from skills acquisition to constraint identification.”
José Parra Moyano
Professor of Digital Strategy
As AI tools and agents become embedded across organizations, the most successful leaders will be focused on how humans add unique value. Executives should stop asking, “Which skills do we need for AI?” and start asking, “What becomes our bottleneck once AI succeeds?”
This shift matters because new skill acquisition only helps when these skills mitigate actual constraints. As AI removes old limitations (time, scale), new ones emerge (accuracy, effectiveness). AI should not just make us faster, but help us think better, using large language models (LLMs) to spark deeper conversations and uncover blind spots. To maximize value, humans must frame questions with precision, then use AI to challenge assumptions.
The bottom line: It is not whether you use AI, but how. In 2026, executives should shift their focus from simply deploying AI for efficiency to identifying the new constraints that AI creates. Only then can they cultivate the human skills that relieve those constraints. When AI takes care of scale and speed, the real bottleneck becomes human judgment, the precision of the questions we ask, the depth with which we interpret model reasoning, and our ability to turn AI-generated ideas into better decisions. The leaders who thrive will be those who develop the skill of identifying the next constraint in the system and then address it with intention and clarity.
“We will see the rise of AI-native departments, especially in HR, procurement, and customer ops.”
Michael Wade
Professor of Strategy and Digital and Director of the Global Center for Digital and AI Transformation
AI-native departments will be functions where 40–60% of day-to-day activities are executed autonomously by AI systems, with humans stepping in for interpretation, escalation, and interpersonal elements. HR, procurement, and customer operations will lead the way.
In HR, the sourcing-to-onboarding pipeline is already being automated end-to-end. Candidate screening, role matching, interview scheduling, onboarding workflows, and training pathway design are shifting into agent-driven automation. HR business partners will increasingly focus on areas where humans excel: employee well-being, conflict resolution, coaching, and culture shaping.
Procurement is moving even faster. Autonomous agents can now monitor supplier performance, scan for geopolitical and compliance risks, draft contract language, conduct competitive bidding, and recommend negotiation strategies. Humans remain critical for final decisions, but the operational backbone becomes software.
Customer service operations, particularly in telecom, retail, airlines, and utilities, will adopt “agent-first service.” In many companies, the first line of support will be fully AI-driven by 2026, with humans handling exceptions or relationship-sensitive cases.
These AI-native departments will set new expectations for productivity, responsiveness, and cost efficiency. Organizations that fail to reach this level by 2027 risk being structurally uncompetitive.
Changing workforce
“By the end of 2026, many organizations will have more AI agents than employees.”
Professor of AI, Analytics, and Marketing Strategy
“Middle management compression becomes real; expect a 10–20% reduction in roles.”
Michael Wade
Professor of Strategy and Digital and Director of the Global Center for Digital and AI Transformation
For years, companies have debated whether AI would eventually replace middle managers. In 2026, we will see the first tangible evidence. Organizations in sectors such as financial services, consumer goods, and pharmaceuticals are already redesigning workflows around AI systems (generative and agentic) that handle reporting, forecasting, analysis, and follow-up tasks automatically.
The result will not be a sudden wave of layoffs but a gradual compression of the traditional middle layer. Instead of overseeing 10 analysts, a manager may supervise a smaller team supported by AI agents that carry out routine work. Roles organized around information routing, basic coordination, and document summarization will shrink. I expect to see a 10–20% reduction in traditional middle-management positions by the end of 2026.
A second shift will accompany this: the move from “I-shaped” professionals (deep functional experts) to “T-shaped” leaders who combine depth with cross-functional capability. Organizations will increasingly prioritize managers who can connect AI, data, operations, and human judgment, which will reduce demand for narrow functional experts.
The largest reductions will occur among reporting-heavy roles in finance, compliance, supply chain planning, and procurement. Companies with more than 5,000 employees will cut 15–25% of mid-level reporting roles as these workflows become AI-native.
Yet the picture is not purely negative. A new management model is emerging. The most successful leaders will act as “player-coaches,” combining hands-on expertise with oversight of hybrid teams made up of both humans and AI. These managers will excel at orchestrating processes rather than controlling them, ensuring that human judgment and machine intelligence interact seamlessly.
Heightened risks
“AI-generated fake news will surge in 2026 – presenting a significant governance challenge.”
Jialu Shan
Research Fellow at the Global Center for Digital and AI Transformation; Associate Research Director at the Center for Future Readiness
Not only will we see a jump in fake news generated by artificial intelligence, but the risks will be far greater than expected. With models like OpenAI’s GPT-5 and Sora 2, Google’s Gemini 3 and Veo 3 driving ultra-realistic, full-stack synthetic media, brands may confront fake product videos, fabricated CEO messages, and AI-stitched reviews that spread faster than teams can react.
Algorithmic amplification will intensify the threat of fake news as visually compelling misinformation outperforms verified content. Under mounting economic and regulatory pressure, companies will be forced to deploy multimodal monitoring tools, rapid-response protocols, and platform partnerships. The shift from text-based misinformation to high-fidelity synthetic media will become a defining governance challenge of 2026.
How to win
“An AI reality check will separate pretenders from transformers.”
Didier Bonnet
Professor of Strategy and Digital Transformation
2026 will mark AI’s “put up or shut up” moment for large enterprises. Economic headwinds and geopolitical uncertainty, maybe amplified by an AI stock correction, will drive accountability and polarization among large firms.
Firms bogged down in their proof-of-concept theater, with little pilot-to-production conversion benefits to show, will succumb to board and market pressures and retrench. Executive statements and press releases may continue to praise AI trials, but actions will speak louder. Leading firms will reallocate funds to fewer but deeper transformations, with the bulk of the investment increasingly dedicated towards organizational, rather than technological change.
Winners realize that AI is a long game and requires unglamorous heavy lifting around data governance, process redesigns, system integration, upskilling, workforce transitions, and board-backed patience for maybe longer, but more impactful, payback. In 2026, the discourse will shift from “telling” to “showing.”
“With AI investments, learn to walk before you can run.”
Robert Hooijberg
Professor of Organizational Behavior
With all the hype and bold predictions of AI replacing key functions and jobs, it is good to remember to walk before you run. Executives who focus on small, problem-solving wins with AI, rather than those who focus on AI moonshots, will be the winners in 2026. Amid economic unrest and geopolitical uncertainty, leaders who prioritize tackling small but meaningful headaches and opportunities will win trust with their companies and workers. The small wins will build confidence, engagement, capabilities, and new opportunities. This then sets the foundation for productive and meaningful use of AI.
“This is the era of the COO: the highest ROI will come from deep operations, not customer-facing AI.”
Michael Wade
Professor of Strategy and Digital and Director of the Global Center for Digital and AI Transformation
This shift is perhaps the most counterintuitive. While marketing, sales, and customer experience functions generate headlines, the greatest and fastest return on investment in 2026 will come from AI embedded deep in the value chain, particularly in supply chain and core operations.
Organizations will focus their AI activities and investments far more on cost minimization, cycle-time reduction, error elimination, safety improvements, and productivity gains than on creating new revenue streams. For most companies, the next 12–18 months will be about efficiency, reliability, and resilience, not moonshot innovation.
Together, these shifts signal a new organizational logic. As AI becomes more embedded in organizations’ structures and systems, the COO will become its most influential champion within the C-suite in 2026, overtaking the CIO, CTO, and CMO in many companies. Organizations that prepare now, by redesigning workflows, upskilling managers, and identifying where autonomous operations can deliver disproportionate value, will be the ones who define the competitive frontier of 2026 and beyond.
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