DevoteamInsightsExpert ViewAI is repricing consulting: Outcomes over time are the premium

AI is repricing consulting: Outcomes over time are the premium

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  • Benjamin Clark Lødemel
    Management Consultant

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For years, premium consulting was defined by insight. Teams assembled evidence, tested hypotheses, and presented recommendations to executives. Generative AI has disrupted this production function. AI Models now synthesise research, generate scenarios, and produce executive-ready presentations in minutes. Strategy remains valuable, but the marginal return on producing strategy artifacts has declined because machines now share part of that work.

This shift is visible in how top firms are reorganising. Reporting on McKinsey describes a portfolio where roughly a quarter of its work is outcomes-based, with revenue increasingly tied to delivery rather than advice. The firm has also deployed about 12,000 AI agents to support consultants, automating research, slide drafting, and elements of project management. These moves suggest that AI is altering the economics of consulting, shifting the emphasis from deciding what to do to making it work in reality (The Wall Street Journal, 2025).

When Good Ideas Go Sideways

Time is a crucial but often overlooked dimension in this transformation.

  • Short strategy cycles are common in the industry, and independent guides place typical MBB engagements at around eight to twelve weeks, with projects sometimes lasting only a few weeks and rarely more than several months (CaseCoach, 2023).
  • Enterprise change follows a different rhythm. ERP programs are a useful reference point because they combine process, data, and behavioural change. Panorama Consulting’s 2024 ERP Report indicates a median timeline of 15.5 months, while its 2025 update notes that timelines are trending down toward nine months on average as SaaS adoption rises, yet still clearly span multiple quarters (Panorama Consulting Group, 2024; 2025). AI can compress pieces of the delivery cycle, for example, with automated testing, data migration aids, and predictive analytics, but those accelerations do not eliminate the longer arc of organisational adoption.

Adoption remains the decisive factor

Gartner forecasts that by 2027, more than 70 percent of recently implemented ERP initiatives will fail to meet their original business case goals. The reasons are rarely technical alone. Misaligned processes, weak governance, limited training, and stakeholder resistance are frequently to blame. Even as AI accelerates pilots and forecasting, the constraints remain organisational. The critical questions shift from whether the technology works to where the model sits in the workflow, what governance supports trust, and which behaviours must change for value to appear in the P&L (Gartner, 2024a; 2024b).

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A 2025 study associated with MIT reported that approximately 95% of corporate generative AI pilots fail to deliver measurable business impact.

Benjamin Clark Lødemel
Management Consultant

Recent research reinforces this view. A 2025 study associated with MIT reported that approximately 95% of corporate generative AI pilots fail to deliver measurable business impact. The study’s coverage indicates that successful cases narrow their scope to concrete problems, integrate AI into existing workflows, and invest in training and change management, whereas most failures stem from weak integration and insufficient adoption capabilities, rather than model performance itself (Fortune, 2025; Tom’s Hardware, 2025). Read our full guide on why AI projects fail.

The Delivery-Native Advantage

This is where outcome-native consultancies have an advantage. My early experience at Devoteam has illustrated this clearly. The firm’s heritage lies in embedding capabilities rather than simply advising. Its strategic plan outlines an ambition to lead in AI-driven technology consulting through 2028, with a growing share of work that is AI-related and outcome-focused. Partnerships reinforce this orientation. Devoteam has been recognised with multiple Partner awards. These partnerships matter because they allow customers and consultants to work directly with AI-native platforms rather than bolting AI on as an afterthought.

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Companies that combine consulting expertise with strong capabilities in cloud, data, security, and change management are better aligned with the longer arc of transformation, where value is realised.

Benjamin Clark Lødemel
Management Consultant

The structure of delivery is equally important. Firms oriented only around strategy feel the ground shifting as AI compresses analysis cycles. By contrast, those that combine consulting expertise with strong capabilities in cloud, data, security, and change management are better aligned with the longer arc of transformation where value is realised. Devoteam’s integration of its management consulting arm with deep delivery through a partnered approach (AWS, Google Cloud, Microsoft, ServiceNow and more partners) proves this point. In projects such as ERP modernisation, AI can speed up testing and automate data migration, while consultants ensure that stakeholders understand the change, adopt the tools, and measure benefits against business outcomes. These dual capabilities make it possible to capture the full value of AI.

Selecting Partners Requires to Ask a New Set of Questions

For clients, this evolution suggests a new set of questions when selecting partners in the AI era. If AI can generate numerous options, the differentiators become sharper. Can the partner build and operate the solution on the client’s stack, including governance, security, and AI integration? Can they help employees adopt and trust AI tools, with training, workflow redesign, and clear guardrails? Will they share risk by tying at least part of their fees to outcomes rather than hours billed? These are time-aware questions because implementing and adopting AI-enhanced systems almost never concludes within a single quarter.

For consultants, the implications are equally significant. The competitive edge now lies in bridging strategy and execution, moving fluidly from the boardroom to the backlog to the change plan. AI will continue to accelerate preparation and analysis, but the human differentiator will be enabling organisations to change their behaviour on Monday morning and sustain that change over the long term. That requires not only technical literacy but also the ability to design adoption paths that make AI trustworthy and sustainable in practice.

In conclusion, AI is not eliminating consulting but rather repricing it. Insight is becoming table stakes, while the real premium lies in outcomes that are implemented, adopted, and measured over time. Some firms are only now pivoting into this model. Others, such as Devoteam, have been positioned there from the start. With an outcome-first heritage, strong cloud partnerships, and explicit investment in AI capabilities, Devoteam is particularly well-positioned to thrive as this repricing accelerates. Discover our Tech Consulting services.

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