AI tips for consultants: be transparent and understand your value proposition

AI is changing the landscape of professional services, not least for management consultants. From streamlining workflows to offering new kinds of value for clients, the potential is huge – but so too are the risks and responsibilities. So, how can independents embrace these tools effectively and safely?

The ‘why’ before the ‘what’

Zoe Webster, an AI consultant who advises organisations on strategy, governance and practice, cautions against jumping straight into tools. 

“It feels like a controversial thing to say, but I don’t think there are any AI tools and platforms that are truly essential besides the search engine,” she explains. Instead, she encourages consultants to pause and ask what really matters: productivity, delivery speed, quality of outputs, competitiveness, customer diversification, staying up-to-date or managing risk.

Her advice is clear: “Focus, start small and experiment. Once you’ve refined your need, there are plenty of tools out there to try at different price points. Ask your network what they use for specific tasks.” 

By aligning AI use with clear business goals, consultants can avoid the common trap of chasing shiny new platforms without measurable outcomes.

Tools for the everyday

For day-to-day efficiency, simple AI-enabled platforms can already make a difference. Joe O’Mahoney, professor of consulting at Cardiff University, who has worked as both a corporate and independent management consultant, advises independents to keep things straightforward. 

“I would suggest using an AI notetaker like Fireflies, Otter or Fyxer and building out AI chatbots via Google Gems or GPTs for specific scenarios such as data analysis, proposal writing or email drafting,” he says. Automating notetaking or leveraging chatbots for draft creation can save hours, freeing up time for analysis, synthesis and client interaction.

Zoe agrees there are “great opportunities to use AI for quality and speed” in such tasks but reminds consultants of the risks: AI is not always right or objective. Meeting summaries, for example, must be checked for accuracy, completeness and bias by someone who was in the room. The same is true for AI-driven research. Sources must be validated before forming the basis of any recommendations.

Transparency and trust

Ethics and professional responsibility remain at the core of consulting, even in the age of AI.

“Consultants should consider being transparent about their use of AI for client engagements, where AI outputs have a material impact on deliverables and when AI is directly interacting with a client,” says Zoe.

The distinction matters: using AI to polish a report may not require disclosure, but using it to assess risk or categorise clients absolutely does.