Consultants point to ‘AI-fatigue’, and organisational overhauls in their predictions for 2026
After another year of uncertainty, 2026 looks set to be rife with economic, political and social challenges that may impede business performance. To help clients and consultants alike prepare for the future, experts from a range of different specialisms have offered their views on what the key to thriving in the 12 months may be – once again, with a particular emphasis on technology.
2025 was a difficult year for the consulting sector. Depending on the definition of the market, consulting in the UK either saw flat growth, or negative growth – and its worst performance since the lockdown period in either case.
As the largest consulting firms in the UK – the Big Four of PwC, Deloitte, KPMG and EY – continue to contend with lower demand, layoffs have continued, and student intake has reduced. While to some degree this has been played off as the result of ‘AI innovations’ taking those roles, a sense pervades that this isn’t as voluntary a process as has been painted.
But not everyone is in the same situation. Many smaller and mid-sized firms have happily availed themselves of young talent now being passed over by the apparently ‘future-proofing’ top table of consulting. With headcounts across the mid-market now booming, these firms will hope that have positioned themselves well to take advantage of rising demand in 2026 – with new challenges arising from clients still struggling to realise returns on heavy technological investments; and a general dissatisfaction with a perceived ‘one-size-fits-all’ bag of tricks brought by the largest firms.
Amid this, Consultancy.uk has reached out to consultants across the sector, to get their takes on ‘AI-fatigue’, new training demands, and opportunities for clients and advisors alike in 2026.
Jonathan Kahan, co-founder, Quartz Labs
AI will no longer be a technology challenge, but an organisational one.
With 95% of AI pilots failing, the C-suite is entering 2026 with growing AI fatigue. But the issue is not the technology. It is organisational. Outdated habits, slow approvals and legacy decision-making models are blocking what AI now makes possible.
So far, most AI use has defaulted to a chat interface. But is chat the right medium for complex decisions, collaboration or creative work? Should AI behave as a tool, a co-worker, an assistant that moves across applications or something embedded directly into every workflow? And once you answer that, a second question emerges: how should teams work with AI together?
Do organisations let every employee use AI as they see fit? Do they augment existing workflows? Or do they redesign the operating model entirely?
Next year will not be about buying more AI, but about building a business that can actually use it.
Nick Merritt, UK executive director, Designit
By 2026, financial institutions will stop treating AI as a silver bullet and start demanding quantifiable ROI. The pressure from Boards and regulators will shift investment from “experimental” to “explainable” AI. Retail Banks will move away from flashy generative assistants and focus on automating the unglamorous but high-volume processes, like onboarding, KYC, compliance checks, and internal reporting.
Insurance will follow suit: instead of chasing “AI underwriting”, the focus will move to data accuracy and automation of claims handling. The lesson will be that the value of AI depends on the quality of the plumbing, not the brilliance of the interface.
Commercial banks will double down on decision support and scenario modelling, particularly for credit and risk, but those tools will have to process resilience under scrutiny. CFOs will demand the same financial discipline from AI initiatives that they expect from any Capital Investment.
In summary, 2026 will mark the pivot from hype to hygiene. Where AI’s worth is proven in operational efficiency, not headlines.
Fernando Ventureira, CEO, Stratence Partners
The era of abstract strategy is over. The era of AI-accelerated, commercially grounded, results-driven strategy has fully arrived.
Across most industries, return on commercial investment will remain a permanent board-level priority. AI, automation, and advanced analytics will be broadly deployed; but only where they deliver visible, repeatable, and auditable commercial impact, not experimental innovation. In 2026, markets will reward those who master speed, quality, AI-enabled execution, and outcome certainty.
Growth will come less from volume expansion and more from portfolio rigor, targeted commercial allocation, and superior productivity across the entire revenue engine – increasingly orchestrated through advanced analytics and automation. Another defining shift in 2026 will be the clear dominance of execution over planning. Operating models, incentive structures, and performance management systems are therefore being redesigned for speed, accountability, and predictable results, with AI embedded directly into both decision and execution workflows.
Scale alone will no longer protect performance. Competitive advantage will be defined by decision precision, execution velocity, outcome certainty, and the strength of the commercial engine.
Commercial Excellence will become the dominant driver of profitability, cash generation, and valuation. It is no longer a sales initiative. It is evolving into a fully integrated, AI-augmented enterprise performance system, encompassing segmentation, route-to-market design, pricing, incentives, and customer profitability management.
Arthur Mansourian, senior manager of global operations, NMS Consulting
In the next stretch, a lot of consulting work is going to feel less like a one-off project and more like something you can “switch on” and keep using. On the ground, that shows up as standardised diagnostics, data pipelines, and playbooks that are reused across clients, then lightly tailored rather than rebuilt. You can see this in the way big firms talk about platforms, industry solutions, and “as a service” offerings, and in the way boutiques are carving out narrow problem areas where they can sell a tight, product-like package.
For individual consultants, that means less time reinventing slides and more time making sure the thing the client bought actually works in their real life: data is flowing, people are trained, business rules are tuned, and someone owns the roadmap after go-live. It also changes careers inside the firms. There is more demand for people who can operate and improve a repeatable offer over time, not just design a solution and move on to the next client.
Another theme that looks set to dominate is heavy, regulation driven change. Climate disclosure, ESG rules, AI governance, data privacy, and sector specific regulation are piling up, especially for global companies. Boards know they cannot treat these as side topics anymore because investors, lenders, and regulators are asking very direct questions about risk and resilience.
For consultants, this turns into messy but important work. Clients need help turning broad rules into specific controls, reports, and systems. That might mean building emissions and supply chain data pipelines that hold up under assurance, putting real guardrails around model use, or reworking operating models so new obligations sit inside everyday processes instead of off to the side.
The tone in these projects is more “help us stay out of trouble and still make money” than “help us write a glossy report.” The teams that thrive here will be the ones who can sit with the CFO, CRO, legal, and operations together and talk calmly about trade-offs, numbers, and timelines, then stick around long enough to see the new ways of working actually bed in.
João Miguel Rodrigues, Lilian Sachtleben, and Kilian Scheuber, consultants, Oliver Wyman
The role of the advisor is being fundamentally rewired. AI now does the heavy lifting in prospecting, prioritising time, portfolio design, planning, idea generation, and service. Clients are using AI copilots to benchmark fees and flag mis-selling in real time. Information advantages that banks had are disappearing. Instead, advisors focus on the moments when emotion moves money and families make irreversible choices, and on helping clients navigate trade-offs that the smartest bot cannot resolve.
Coverage ratios rise because systems prepare, execute, and follow through. Governance shifts from supervising individuals to supervising algorithms and entitlements. White-glove service becomes rarer, more valuable, more explicit, and more transparently expensive.
For the C-suite: invest in technology that enables scalable, personalised advice and reduces the administration burden on advisors, then hire, train, and pay for expertise in guiding families through crisis and complex governance decisions. Aim AI and analytics at client-positive use cases, including better recommendations, clearer disclosures, and cheaper ways to reach the same outcome. Shift headcount from manual preparation to the design, calibration, and control of advice intellectual property.
Shaun de Caires, technology consulting director, Gen25
AI continued to accelerate in 2025, but for many organisations the real challenge was not the technology itself: it was the uncertainty that it could bring scaling it into production. Many pilots got stuck, only a fraction of initiatives achieved clear ROI and companies struggled to move from proofs of concept to real impact. 62% worry about unpredictable AI costs and 64% say TCO is unclear. This raises an important question: how do organisations move past this barrier?
At Gen25, we embrace navigating uncertainty rather than trying to control it. The more firms try to lock down outcomes, scope and budgets upfront, the harder it becomes to forecast the real value of AI initiatives.
The companies that make progress start with tightly defined outcomes, build adaptability into their approach and measure value continuously. However capable an AI model is, it will not hit scalable performance when confronted with poor data, unclear governance and missing accountability.
In 2026, organisations will need to treat AI agents like digital employees, each with a job description, performance metrics and clear scale-or-stop rules. Governance will become a growth enabler rather than a compliance checkbox. Firms with embedded guardrails, clear responsibilities and live monitoring will scale AI faster and with more confidence.
At the same time, leaders will return to the fundamentals: high-quality, connected data. Without reliable context, no agent can perform well. And talking about performing; think about outcome KPI’s like deflection % for case triage, CSAT uplift in customer experience or conversion rate increases in a sales journey. This is why 2026 will reward a different kind of AI leadership. Success will not come from trying to eliminate uncertainty, but from learning to work with it. The organisations that embrace uncertainty as part of the process, and turn it into informed and measured progress, will be the ones who gain real competitive advantage.
Nelson Sivalingam, CEO, HowNow
We’ll see a shift from T to M-shaped skills next year as organisations look to build employee skillsets across multiple domains. AI is increasingly able to replicate the deep expertise that once defined T-shaped talent. When specialist knowledge can be automated or augmented so effectively, its value – while still important – is no longer what sets people apart. What AI cannot yet do is integrate insights across domains, apply judgement in ambiguous contexts, or connect dots that don’t obviously belong together.
That integrative, cross-disciplinary intelligence is uniquely human, and it’s becoming the new competitive advantage. This is why we’re seeing a shift towards M-shaped skills: people with depth in key areas but also adaptability, cross-functional literacy, and the ability to bridge disciplines.
Organisations are already changing how they hire and develop talent as a result, prioritising those who can navigate complexity, collaborate across boundaries, and pair AI-enhanced expertise with human-level problem-solving. Companies increasingly need designers who can think like product managers; product managers who can think like engineers; and engineers who can think like designers. In response to this, employers will accelerate cross-skilling and upskilling across multiple specialisms next year.
Alongside this, employees are looking for new ways to deliver value, stay relevant, and compete with AI itself. AI can now write brilliant code so if the only thing an engineer can bring to the table is coding, they will become obsolete. Organisations want (and need) people who can shape and deliver the end product experience - and that requires the right mix of human insight, expert knowledge, and an ability to join the dots between different domains.
Jon Bance, COO, Leading Resolutions
‘AI won’t replace you, but someone who uses AI will,’ is a phrase lauded confidently and frequently in the past year. However, what’s also true is that companies that embrace AI to help train new employees and better serve their customers will outpace those who don’t.
Human talent, expertise and experience cannot be replaced with AI, so it’s crucial we continue to nurture the next generation of talent. By 2026, AI-enhanced consultancies will dominate the mid-market, using data-driven insights to deliver faster, more precise recommendations. The “challenger consultancy” will emerge as the new model: agile firms blending human intuition with machine intelligence to outperform the Big Four.
It’s time to get out of the lab in 2026 and speak with customers. Artificial intelligence will no longer be a lab experiment, but the engine of modern enterprise and organisations need help from agile AI centric challenger consultancy to drive out value.
Transformation should be customer-driven and empowered with AI, not AI-driven. When serving customers is the priority, businesses grow faster. Integrating AI into transformation increases the business’s resilience to changing technologies and ultimately supports a more profitable exit strategy.
Rebecca Harness, CISO, Deltek
The more connected project operations become, the more critical it is to design for continuity. Cloud and SaaS platforms have unlocked agility and collaboration but leaders also need to plan for confident delivery, even in the event disruption. That means investing in operational redundancy, clear communication protocols, and hybrid systems that ensure continuity when core platforms are unavailable.
When projects keep progressing, data stays accessible, client confidence remains high, and teams can switch seamlessly to backup workflows. When deadlines and reputation go hand-in-hand, this mindset turns resilience into competitive advantage.”
At the same time, security in this environment must be viewed as an enabler of growth. For too long, security has been seen as the department of slow progress or adds friction to transformation. In reality, it’s the opposite. When designed with intent, security is the foundation that unlocks innovation. It allows organisations to move faster, experiment safely, and deliver with confidence.
In project-based industries where data integrity and client trust are critical, embedding security into the design of systems and processes doesn’t limit creativity, it protects and amplifies it. Security should be seen as a catalyst for continuous progress.”
Tom Heyes, practice manager, Airwalk Reply
Through 2026 we predict the Minimum Viable Business (MVB) to become a genuine operating model within financial services organisations. The resilience narrative will move further away from restoring IT systems, to sustaining critical services through disruption, with the defining shift from “systems back online” to “customer outcomes still delivered”, e.g. payments processed, trades confirmed, customers supported; even when parts of the IT estate are impaired.
We expect cross-industry collaboration to grow for financial services resilience, with an increased appetite for peer and substitution arrangements developed for critical customer and market facing services. Consultancies will continue to play a key role in connecting firms to address cross-market problems, alongside industry forums and events, particularly in a thematically non-competitive arena such as resilience.
Technology architectures will continue to evolve, with data resilience playing a greater role in mainstream decision making. Functionality such as rapid rerouting, tertiary immutable storage and substitutional systems will become the baseline, alongside traditional functions for site, region, zone or supplier redundancy. The resilience differentiator will become your ability to act upon recoverable data to maintain MVB services rapidly, rather than recover the tech stack.
Building these capabilities in a sustainable way depends on living dependency intelligence, replacing static maps and one-off assessments with continuously monitored views of services, systems, data and suppliers. We see Configuration Management as a top-priority for CTOs and CIOs in 2026 as we work to connect and enhance the quality of operational data which underpins effective internal AI adoption.
Finally, resilience testing will become more realistic and business-led, proving whether MVB and substitution actually work under duress. Expect more testing and war-gaming outside the annual failover test that puts you in the driving seat of a failure scenario at all levels of the organisation. This will include new AI-led hyper-personalised simulations and deep scenario experiences that really put resilience plans through their paces, think ‘escape room for business continuity!’.
Abi Wareing and Rob Ellison, partners, Cortex Reply
As we enter 2026, the AI conversation will shift decisively from small-scale experimentation to embedding autonomy. The hype around copilots and assistive tools is already flattening and organisations are realising what many suspected: tools that simply help people work faster are not transformative. The real breakthrough lies in AI systems that operate as additional team members, working end to end, independently, and continuously.
This marks the rise of agentic AI. Those that delay will be rapidly overtaken by organisations adopting autonomous, multi-agent systems capable of running real operational workloads. These systems will quietly execute workflows, orchestrate decisions, maintain compliance, and resolve issues before humans even notice. They will not ask what to do next - they will simply do it.
However, this shift demands change. Repeatable processes provide a foundation, but most organisations must refine and formalise them so autonomous systems can operate without constant intervention. Data, security, and governance models will need rapid evolution. Concepts like “manager-in-the-loop” will reshape team operating models, with employees becoming managers not of people, but of the agentic colleagues working alongside them.
2026 will be a year of divergence. Those investing in agentic automation will begin to redesign operations around scalable, intelligent systems. Those clinging to assistive tools will remain stuck with manual checkpoints and rising costs, watching competitors deliver faster, cheaper, and more accurate outcomes. Agentic AI is no longer an experiment - it is the next operating model.
Toni Marshall, managing partner and CEO, Skarbek
2026 won’t be about bold strategy statements – it will be about execution. After years of enjoying generous margins, pharma now faces a new reality: US policy is beginning to push prices down, impacting GM and EBITDA margins. Efficiency isn’t optional anymore, it’s essential.
Patent cliffs, increasing R&D costs and AI investment are colliding with political shifts and China’s growing influence in drug development. Moderate growth will not disguise the fact that operating models built for a different era are no longer fit for purpose.
The winners will act decisively: simplify structures, cut decision layers and create agile innovation engines for both traditional and emerging therapies. AI must move from pilot to production, delivering cost efficient and measurable gains. Boards will demand transparency, speed, clear ROI and leadership teams equipped for change. Expect a wave of talent migration from the tech world as companies hardwire agility into their DNA.
In short, resilience, alignment and ruthless cost discipline will define the next chapter. Those who treat operating model redesign as a strategic weapon will not just survive margin pressure – they will turn volatility into a competitive advantage.
