The future of consulting in the AI age: technology is ready, organisations are not
As consulting firms pile pressure on partners to adopt AI into every aspect of their work, new research from Ajuno suggests that companies will not see the technology’s true benefits until they move this transformation beyond individual uptake. According to Will Barnes, Ajuno co-founder and co-author of the report, leading companies deploying AI focus on overhauling operating models and governance, to empower the technology’s use by staff.
A recent statement from PwC’s US leadership - that partners resisting AI “have no place at the firm” - captures the mood of the market. At the same time, the CEO of Microsoft AI, Mustafa Suleyman, has suggested that most professional, computer-based tasks could be automated within 12-18 months.
New research from Ajuno argues something more provocative: the technology may be ready, but organisations are not. While the direction of travel is clear, the misunderstanding is the speed.
Consulting, a sector that shapes strategy and transformation across nearly every industry, is now at a structural inflection point. In the UK alone, it supports the vast majority of FTSE 100 companies - and its influence continues to grow. According to recent industry data, 73% of consultants now identify AI as the single biggest shift facing the profession.
However, while AI capability is advancing rapidly, most firms are still treating it as a productivity tool, which is leading to limited bottom-line impact. Those seeing meaningful gains are not simply deploying AI, they are redesigning operating models, governance and accountability. And that transformation is unfolding over a three-to-five-year horizon, not 12 months.
Four pathways, not one future
Our research sets out four distinct pathways for how AI may reshape consulting. Each has a unique set of questions to ensure best outcomes.
The ‘embedded partners’ path sees AI disappear into workflows, quietly shaping analysis, presentations, and decision-making. But those on this path need to consider, if AI is invisible, how do you measure value – and who is accountable for it? ‘Avatar teams’ by contrast see AI become visible: with digital consultants joining meetings, interacting with clients, and building trust over time. In this case, firms must face the question, when clients trust the avatar, what happens to the human consultant?
Elsewhere, ‘autonomous firms’ moving beyond this will see clients engage directly with AI consultants, supported by networks of agents delivering work at scale. This bodes some uncertainty in terms of accountability, as if outcomes are delivered by systems, where does responsibility sit when things go wrong? Finally, ‘consulting engines’ will see applicable firms become “always-on” – with consulting evolving into a continuous, embedded capability operating like enterprise software. But in that case, what is a consulting firm when there are no projects, only persistent systems?
With the majority of AI implementation still considered ‘experimental’ in its nature, most organisations today sit firmly at the “co-pilot” stage, experimenting with tools rather than committing to a direction. But with investors looking to see returns, the risk is not choosing the wrong path, but failing to choose at all.
When it goes wrong
If the upside is significant, so too are the risks. Recent events highlight how quickly things can unravel, such as the widely reported hacking of McKinsey & Company’s leading AI platform in March 2026 - leaking 728,000 files and over 46 million chat messages. As AI becomes embedded in delivery, the impact will scale.
Our research outlines credible and concerning failure scenarios:
- Over-reliance on AI eroding human judgement
- AI-driven reputational damage through uncontrolled outputs
- Legal battles through breakdown of accountability in agentic systems
- Data breaches triggered by interacting agents
These are not edge cases; they are predictable, preventable outcomes when adoption outpaces governance. But the truly central finding of our research is that the barrier to AI adoption is not technology, but rather, organisational change.
Firms must rethink: accountability, and who owns AI decisions; operating models, to optimise how humans and AI work together; skills, to work out what replaces traditional consulting capabilities; and economics, to establish if you selling effort, outcomes, or systems.
Those companies which act boldly - aligning strategy, governance and delivery - are already pulling ahead. Research in late 2025 from McKinsey & Company suggests organisations pursuing enterprise-wide AI transformation are more than three times as likely to achieve high performance.
Those which hesitate face a different future: rising inefficiency, talent loss and increasing dependence on AI-enabled competitors.
What next?
As organisations enter a new financial year, the question is no longer whether AI will reshape consulting - because it already is. The real question is what path is your company on for the next one-to-three years, and what are you building for the next five-to-ten?
Incremental adoption will not be enough. The firms that win will make explicit choices, accept early imperfection and build the governance to scale with confidence. Those that don’t will not stand still – they will fall behind.
Ajuno is a strategy consultancy specialising in drones, robotics and AI for critical national infrastructure - working across water, power, transport, nuclear and emergency services to translate innovation into safer, value‑led operating models. This article is a snapshot of a much broader shift. Ajuno’s full ‘Future of Consulting in the AI Age’ paper provides essential reading for anyone serious about understanding consulting in the AI age - not as speculation, but as a vision of the future to enable critical decisions now.
