90% of management consultants use Gen AI in their daily tasks

Nine-in-ten consultants are using Generative AI for a huge array of tasks – from conducting research, to writing emails, and even creating reports. Research from LexisNexis suggests this is already helping more than one-in-ten advisors to save more than five hours of time every day, which they can redirect towards value-adding activities.

When a client hires a consultant for any engagement, they expect them to already be an expert in their relevant sector. Consultants have traditionally needed to demonstrate deep familiarity with the competitive landscape, and key trends of a client’s business and supply chain, before commencing a project. And to do that, the advisors of old would spend hours reviewing reports, datasets, and news.

Now, though, consultants believe the game is changing, with the advent of AI. Across the consulting sector, firms are adopting AI, asserting that the technology’s speed, consistency and accuracy are helping them raise the standard of their deliverables. For every hour of high-intensity research it helps to condense into bite-size overviews, a consultant can re-allocate their energies to more high-value analysis and strategy-making.

Illustrating this, in 2025, strategy giant McKinsey & Company famously received a commemorative plaque from OpenAI, due to the large number of prompts its experts plumbed into their ChatGPT model. Months later, the firm’s boss Bob Sternfels claimed the company now had 60,000 ‘employees’ – including 25,000 ‘AI agents’.

But this trend extends far beyond consulting’s top table. According to a new study from LexisNexis, consultants of all shapes and sizes are taking to the technology like ducks to water. In the process, they are vastly outpacing AI’s uptake in the wider economy as they seek to boost the results of their clients, as well as their own.

According to a 2025 study by Accenture, more than 80% of business leaders report that Gen AI has exceeded their expectations. By LexisNexis’ reckoning, that average across all industries has risen to 83% now. In contrast, that stands at 91% of management consultants. And while high adoption of AI alone does not guarantee results, the way those firms are scaling their solutions is already paying dividends, the researchers claim.

A 40% chunk of consultants told the firm that they were already seeing a “significant increase” in productivity. While that is still not as high as it could be, it is significantly better than the other finding of the earlier-mentioned Accenture poll, where of the 80% to leverage AI, only 13% said they were now realising value at an enterprise-wide level. Consultants believe the best is yet to come, too. An 85% majority said they expected AI would positively impact their organisation’s overall performance in the future.

Investing in human talent, to make the most of AI

So, what is making the difference for consultants, when it comes to realising the supposed potentials of AI? Why are they struggling to do so less than other types of organisation? According to LexisNexis, the secret may be in the way firms are investing in AI as well as – rather than instead of – human talent.

With more than 40% of consultants having received advanced Gen AI training – nearly triple the average of the wider economy – understanding of the applications of the technology is moving ahead rapidly in the sector. This is partially thanks to the traditional consulting model; regular upskilling was already the norm in the industry, and with 70% of firms conducting training at least quarterly, Gen AI proficiency has quickly become a core component of that professional development. Meanwhile, just 8% of firms report offering no Gen AI training at all, against an industry-wide average of 28%.

Thanks to this advanced understanding of the opportunities AI provides, consultants are already finding key areas where they can put it to work. LexisNexis found that 77% are using it to conduct research, while 71% are using it for summarisation, and similar numbers deploy it to draft or analyse documents – as mentioned earlier. But in the future, a growing number expect time-consuming tasks such as data entry (21.4%), creative content (18.8%) and report generation (12.5%) could be removed from their workload by technology – clearing the way for even more value-adding activities.

Speaking of the time being saved, LexisNexis alleges that consultants are already seeing huge benefits thanks to the implementation of AI. A 14% portion said they saved more than five hours every day, using the technology for repetitive tasks. The largest number of 56% said they saved between three and four hours – while 28% said they at least saved one hour thanks to AI’s implementation.

Safeguarding required

That is not to say that AI doesn’t pose challenges to consultants, or the wider world, however. Consultants will need to adapt their organisational model, because with such a public embracing of AI to save time, client expectations will also shift.

For decades, the billable hour underpinned the economics of consulting, with clients paying for time and expertise – and consulting value therefore being measured by how many hours a firm could stack against a project. Scale was achieved by adding people, and profitability grew with utilisation. But as AI becomes a more prominent part of the equation, some commentators are arguing that consulting’s billing model will need to modernise – and find new ways to demonstrate and charge for the value delivered. Firms which struggle to do so may swiftly find themselves priced out of the market, or undercut by agile new competitors.

At the same time, despite the hype around the ‘revolutionary’ capabilities of the technology, consultants must be aware that they cannot simply assume the quality of an AI’s output is good enough for immediate publication. ‘Hallucinations’, or inaccuracies, aren’t a rare quirk of any AI system, but have rather proven to be a very common occurrence, even after years of development. BBC research into leading AI tools found their news summaries contained “significant issues” in 51% of cases, for example. As a result, putting out reems of quick and easy AI prompted content is not a good idea, even in terms of conventional online marketing.

Above all, though, firms need to take care around issues of data-governance and privacy. As more firms experiment with AI across different functions, but where perhaps businesses lack a cohesive adoption strategy, there is a risk that teams may be left to their own devices. Without guardrails, managers can lose track of where AI sits within their organisation, how it’s being used by each business unit and whether all of this aligns with their compliance requirements.

This is when AI can become a dreaded ‘black box’ in business systems – with the risk being that as it’s not always clear from the outputs of these tools how they got there or what data was used, firms leave themselves exposed to compliance breaches when consumer AI tools are used with sensitive client and employee information. That could be disastrous for a firm’s reputation, its privacy law compliance, and its long-term financial stability – no matter how much time it has saved on admin and data-entry.