Can professional services firms trust AI to help them win, grow, and retain key clients?

  • 07 Jun 2024
Andy Rogerson

Andy Rogerson

In the second of our three-part series, we explore how professional services firms can leverage and trust AI in key client programs.

In the first article in our series exploring how to outperform the market in a world of AI, we revealed how ABM must align to strategic goals to realize the full benefits. We used Momentum ITSMA’s Account Growth Matrix to point us in the right direction.

To achieve our strategic goals, we need to build trust with our key clients. And if we are using AI to move that trust needle, we need to trust AI itself. In the roundtable that provided the impetus for this series, we identified four building blocks to enable this trust (see diagram below). We also pitched some thorny questions to the marketing leaders that attended.

Four building blocks of trust

The first concerned their data assets. How important is data to the partners that are best placed to collect it? Do you have trust in your CRM systems, customer surveys, website analytics, sales reports that you have access to, and the insight that you can derive from them? Is your information reliable for informed decision-making? Do you have accessible and understandable policies? Or is there work to be done to develop the accuracy and data security needed?

Second, to what extent do you trust the team participation and the organization for AI? Is there enough of a culture and enthusiasm to genuinely embrace it? Is AI discussed openly and regularly within the organization? Does it contain your own IP? We previously discussed how difficult it was to develop trust in the ABM process, but when you add AI into the mix, does that make it even more complicated? Most likely. So, how can you show the firm how AI can positively impact business goals and take the partners with you on the journey?

The third concerned marketing technology (martech) and its application in professional services. What is your framework for the development and governance of AI projects within your existing systems? Are you aware of, and fully utilizing, the AI featured in your current martech stack? Are martech vendors showing you where their technology is headed? And are they actively supporting you to get the most value out of what you have?

What is the reality and tension in mobilizing the technology you use, which will most likely involve several components working together? Do partners trust the technology or indeed the rest of the team to use it correctly? Or is there a fear that it may highlight the silos we work in?

And, finally, what about the actual client relationship itself? Is it even possible that AI can enhance something that is so uniquely human – and develop a better, richer, more trusting relationship that could bring demonstrable results? That doesn’t feel like a naturally ‘programmable’ process that can be mapped and enhanced. If AI is going to be the tool that improves how we engage and delight our clients with our marketing, is there a tension there?

Saving time or changing the world?

The attendees had a mixed response to these questions. Several, particularly those from law firms, had set out a charter for the use of AI – a document that articulates what it should and should not be used for. Clearly, professional services firms need to be exemplary with regards to security and confidentiality, and most were. Their biggest challenge, however, was to marry the required technical compliance with the desire to experiment. Many had overcome this by using a private instance of AI in a closed space.

Many professional services firms have been using AI for client work for many years. For instance, to save time on drafting contracts. Paradoxically, this is inherently riskier than using it for marketing and business development purposes. Therefore, we need to change the internal mindset to convey that AI is not there just to improve our core services. It can also drive operational efficiency across the firm.

But attendees believed that there were fewer genuine examples in the sales and marketing realm. None had the ability to use AI to collate all the proof points and examples a partner might need for a conversation with a particular client. Most were still struggling with requests to give them a clear definition, write a paragraph, and embellish a few key points in an email. That is fun but is scratching the surface.

Maybe using the term ‘generative AI’ isn’t that useful and we need different semantics. With generative AI we automatically think about typing a question into a box and getting an answer back. If we were to use a phrase like large language model (LLM) maybe that will surface different and more valuable conversations, exploring automating processes, demonstrating what good looks like, and teaching us about success.

The ultimate goal for our group, however, was to use AI to enable better relationships between partner and client. We ended the conversation with another question. If AI is all about building a better relationship, is it about saving time on the daily workload, which the partners can spend on the relationship or giving them better relationship-building tools? We’ll explore this in our next article.

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Andy Rogerson

Andy Rogerson