How Is AI Changing the Consulting Industry?

Artificial intelligence is reshaping how (some) consulting work is done
LLMs (Large Language Models) such as ChatGPT and Claude, predictive AI that utilises machine learning to create forecasts, and agentic AI – capable of automating and co-ordinating tasks on a deeper level - have combined to become an extremely powerful toolkit for businesses in the last five years. The ability of LLMs to summarise information and draw up plans and frameworks, of Machine Learning algorithms to take historic data and produce valuable forecasts, and of agentic AI to, for example, co-ordinate multiple other AI applications to write code that searches through a database, pulls the data it needs, and write an analysis of it, is invaluable to consultants – it can save countless hours. However, although AI excels in the aforementioned areas, it is limited in its ability to create ideas, manage people, or produce and interpret analysis beyond a surface-level.

The AI hype has died down – now its real potential is being realised
In 2026, the business world, including consulting, has moved past the initial hype of AI. The fledgling, experimental phase beginning with the conception of AI tools that could be business-applicable – but when their potential hadn’t been realised – is over. Clients are no longer excited by the mere prospect of AI-generated work: they want rapid, tailored, dynamic solutions delivered by the lowest bidder. 

Among the world’s largest consulting firms, including the ‘Big Four’ professional services firms (Deloitte, PwC, EY and KPMG), there is something of an AI arms-race developing; between them $10 billion has been poured into AI since 2023[1] – with firms investing in partnerships with AI labs, upskilling staff to be fluent in AI-usage, and even developing proprietary AI platforms. McKinsey began deploying Lilli, its internal AI platform, in 2023; BCG has partnered with Anthropic, developers of Claude; and KPMG has made AI use mandatory for all staff. A variety of AI tools are being invested in: LLMs and Machine Learning have been shown to greatly improve both speed and quality of data analysis, predictive modelling, and forecasting.

And AI seems to be having measurable impact; a survey by Deloitte found that 74% of organisations reported that AI accelerated their data analysis processes, and a separate survey by EY found 84% of business leaders agreed that AI had helped improve their forecast accuracy[2]. A study by Harvard Business School of 758 BCG consultants reported that, when assisted by AI, consultants completed 12.2% more tasks, completed their tasks 25.1% faster, and with 40% higher quality, compared to a non-AI-assisted control group[3]. The gains seen from AI were also reported industry-wide: two-thirds of organisations surveyed in Deloitte’s 2026 Enterprise AI Survey reported measurable productivity and efficiency improvements from AI adoption, and more than half reported enhanced decision-making.[4]

An even larger improvement was seen among consultants who had previously been bottom-half performers, suggesting that AI can be of even greater help to smaller firms and lower-performing consultants than to the biggest names in the industry. This is on top of the fact that AI services available to the public, or to businesses at low cost, have reached a level of sophistication close to being on par with the AI services available only to the largest firms.

The consequences of improved efficiency raise challenging questions for the industry. If AI does save time, increase productivity, and produce work to the same quality as a human consultant, two questions are raised:

 ‘Shouldn’t those efficiency savings be passed on to the client?’ and ‘Why even hire human consultants?’

The first question is already being answered by the industry
Traditional hourly billing is being eroded. Charging clients for hours of labour-intensive work no longer makes sense when that work can be done by AI in mere minutes, so firms are moving toward a variety of new pricing structures. Some have moved to a model where fees are earned by the results the consultant achieves for a client – McKinsey reported that 25% of its total fees in 2025 were earned via this model[5], while others are adopting subscription pricing for access to their proprietary AI platforms, such as PwC and its AI OS platform, with advisory support costing extra.

The second question is also leading to significant change
“Doomsday” was predicted by a 2017 McKinsey Global Institute study: it estimated that 45% of activities performed by consultants could be automated using technology available at the time[6]. And that study came more than 5 years before the widespread rollout and adoption of LLMs. There is certainly evidence of change in the consulting industry’s workforce trends: McKinsey laid off 5,000 employees of its initial 45,000 strong workforce and announced a further 10% reduction in late 2025[7]. This, of course, cannot be definitively attributed to AI, but there is a trend of firms slimming down their workforces, alongside AI becoming more widely adopted. Accenture cut 11,000 roles[8] while simultaneously promising their number of AI-focused roles would reach 80,000[9] in mid-2025. CEO Julie Sweet even warned employees unable to transition into AI-based roles that they would be ‘exiting on a compressed timeline’. And, for Accenture’s bottom line at least, it’s working – they reported 7% year-over-year revenue growth for the June-August 2025 quarter, and a 70% increase in bookings of AI-based projects, from $3 billion to $5.1 billion[10].

AI is not a magic wand – but everyone thinks it is
Despite its merits, AI has real limitations. These include its inability to generate genuine new ideas beyond pulling from already existing work, or to connect with and understand the people and culture of an organisation – and how to get the best out of them. It cannot replace the tacit knowledge of senior, experienced consultants that has been built up through creating and implementing solutions in “real life” business contexts.

In fact, AI across all industries may not be as ready to take over as it seems. A 2025 study by MIT NANDA (An MIT Lab dedicated to AI) found that 95% of organisations surveyed reported no gains at all from implementing AI[11]. However, the study also found that, as a whole, the Professional Services industry saw gains in efficiency, and that the industry was second only to Technology for the largest impact from AI. The gap between AI’s impact on consulting and other industries may end up being beneficial to consultants if potential clients are slow to invest in AI, retrain staff and implement it into their workflows.

Jim Kennedy, co-founder of Cursus (and Interim CPO & Principal Transformation Consultant at MCR), provides valuable insight on this. He observes that organisations often make the mistake of “bolting AI” on to pre-existing workflows – and often within a single function – in ways which fail to address the weak or friction points that may exist in the interaction between business functions or between people and systems. The Cursus solution is to look at the way that outcomes are delivered horizontally through an organisation, one critical workflow at a time – putting people front and centre, and supported by AI.

No, consultants will not go extinct
Human consultants will not go the way of the dodo or the fax machine. Instead, AI will assist humans by doing previously time-consuming, repetitive, mundane work – crunching data, drawing graphs, and summarising documents. This will allow human consultants to focus on higher-level tasks: connecting with clients, assessing and creating strategies, and properly implementing the work done by AI into solutions. Additionally, human oversight on AI-generated work will always be required; AI is known to ‘hallucinate’, and the dangers of erroneous, un-checked AI output has already been realised: in 2025, Deloitte partially refunded the Australian government their $440,000 fee for a report that contained numerous errors, including references to non-existent academic publications. Following this incident, Australian Labor senator Deborah O’Neill hinted at the previously mentioned possibility of consultants being altogether bypassed by AI “Perhaps instead of a big consulting firm, procurers would be better off signing up for a ChatGPT subscription.”[12].

Is the AI revolution another ‘Digital Revolution’?
Randal Tajer, Financial Services Practice Lead at MCR, observes that while AI’s potential may help to “provide solutions to problems that haven’t been thought of yet”, consultants will continue to have a critical role to ask the right questions in the first place. AI should be utilised where it is strongest – where Machine Learning algorithms can be utilised for data analysis, or summarising existing information. Human oversight is always necessary – as Randal says, “no-one is ever going to submit an AI-generated tax return.”

The future of AI’s impact on consultancy is uncertain, but certainly not one of extinction
Instead, the role of a consultant will change. They will take the work of AI, interpret it, connect with clients on a human level, and develop human-focused solutions to organisational and societal challenges. In short, consultancy firms will become more streamlined and senior in profile, and will need to be more ‘AI-literate’, with the ability to use LLMs, Machine Learning and Deep Learning to their full potential.

[1] https://whitehat-seo.co.uk/blog/ai-impact-on-consulting

[2] https://irgexecutivesearch.com/insight/the-emergence-of-ai/

[3] https://www.thecrimson.com/article/2023/10/13/jagged-edge-ai-bcg/

[4] https://www.deloitte.com/za/en/issues/generative-ai/state-of-ai-in-enterprise.html

[5] https://aiweekly.co/alerts/mckinsey-ties-25-of-fees-to-outcomes-as-ai-erodes-billable-hours

[6] https://www.mckinsey.com/~/media/BAB489A30B724BECB5DEDC41E9BB9FAC.ashx

[7] https://www.businessinsider.com/mckinsey-employee-numbers-dropped-5000-consulting-slowdown-overhiring-2025-5

[8] https://www.computing.co.uk/news/2025/accenture-ceo-tells-staff-to-use-ai-or-leave

[9] https://www.klover.ai/accenture-ai-strategy-analysis-dominance-in-it-service-and-management-consulting/

[10] https://www.cnbc.com/2025/09/26/accenture-plans-on-exiting-staff-who-cant-be-reskilled-on-ai.html

[11] https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf

[12] https://www.theguardian.com/australia-news/2025/oct/06/deloitte-to-pay-money-back-to-albanese-government-after-using-ai-in-440000-report