The latest WARC Future of Strategy report is just out and makes for interesting reading. 80% of strategists think the discipline is at a crossroads. Agency jobs in decline, and yet client demand for strategy skills needed more than ever in a volatile world. There also seems to be a split on whether AI will erode the value of human planners, but it’s clearly going to to create momentous change to the way in which strategy and planning is done.
Given this context I thought it would be interesting to map a few plausible scenarios for the role of strategists over the next 3-5 years in the era of AI, and (full transparency) I’ve used AI to help me do the research for this. I defined four key drivers of change that could materially re-shape what strategy work looks like, and within those a few of the essential dynamics.
Technological drivers
- The rate of AI integration into strategic workflows: From augmentation, where AI is more of a co-pilot to planning work, to high automation where AI acts as the primary strategist).
- Quality and accessibility of strategic AI tools: The question of whether tools remain open and democratised or become proprietary, enterprise-locked ‘strategy stacks.’
- Agentic AI maturity: The extent to which autonomous agents can synthesise research, run simulations, and coordinate strategy execution involving lots of variables.
Human and organisational factors
- Trust and adoption mindset: Will strategists see AI as an enabler or a threat to expertise and creativity?
- Redefinition of value: Whether clients and organisations still prize human judgment, narrative framing, and synthesis, or whether they default to algorithmic precision and scale.
- Skill evolution: How quickly strategists adapt to become ‘AI conductors’, skilled in prompt engineering and working with AI, or what you might call ‘meta-strategists’ curating context rather than producing decks.
Market and economic context
- Economic pressure and client expectations: The interesting dynamic between drives for efficiency, which may push strategy toward automation, and increasing uncertainty, which may drive a heightened appetite for deep human insight.
- Consulting and agency restructuring: How professional-services models evolve, for example towards smaller, high-impact strategy boutiques (the WARC survey noted that strategy independents were growing) or towards AI-augmented mega-platforms.
- Regulation and data governance: The spectrum between tight and permissive regulatory regimes which may shape access to proprietary data and synthetic insight generation.
Societal and cultural shifts
- Cultural valuation of human creativity: Whether ‘human originality’ gains premium status (as with craft and artistry) or it becomes secondary to speed and optimisation.
- Ethical and accountability expectations: Who owns decisions made by AI-augmented strategists? Ethical oversight could become a differentiator.
- Evolving client-agency relationship: Again, a spectrum from commissioned deliverables to continuous, data-driven advisory loops.
There’s several big themes running underneath these four dynamics. The proliferation of autonomous AI agents running real-time market sensing and strategic scenario simulation. The commoditisation of data synthesis, which may push strategists toward narrative framing and organisational influence. The shift from strategy as a deliverable to strategy as a continuously learning system. The growth of AI-literate creative generalists and polymaths replacing traditional silos, and the emergence of new ethics-of-judgment roles.
So to try and articulate these I’ve defined three 2 x 2 frameworks which map the key dynamics and which can help us think about potential future scenarios for the future of planners and strategists.
Framework 1: The human–machine balance
This model looks at how the pace of AI adoption interacts with the strategist’s willingness (and ability) to evolve their practice. So the axes focus on the degree of AI integration against the level of human trust and adaptability in relation to AI.
I think these scenarios highlight how attitudes, trust and mindsets around AI may be as significant as capability in how it ends up becoming integrated into the work of the planner.
Framework 2: Strategic value
This one explores how AI reshapes the economics and output of strategy, and the existential question of whether it becomes commoditised through platforms, or elevated through narrative and judgment.
This one I think is interesting because it looks at the business model impact and implications, and it asks the question of whether strategists become industrialised or artisanal, and whether AI is applied primarily in the context of scale or intimacy and understanding.
Framework 3: Control and creativity
The final framework considers how another important dynamic, the structural forces of ownership, access and openness, intersect with creative ambition. This is really about who owns the tools and what they’re optimising for.
This lens is more structural, showing how power and ownership could redefine not only what strategy does but who gets to do it.
Looking at these different dynamics and scenarios for how the future could play out for strategists I think it’s very true to say that the discipline stands at a real crossroads. On the one path, strategy risks becoming increasingly automated and procedural, a process optimised by algorithms, efficient but hollow, where human judgment is reduced to validation. On the other lies a more imaginative, human-centred craft, one that uses AI not to replace thinking but to expand it, combining machine intelligence with human curiosity, empathy, and narrative sense-making.
The difference between these futures will depend less on technology itself and more on how strategists choose to redefine their value: as operators of systems or as orchestrators of meaning. The next few years may prove whether strategy becomes an input to optimisation, or remains a discipline of interpretation, foresight, and imagination.
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