AI for marketing and business development.
Some firms are talking about it, others planning it, others piloting it — and a few fudging it. But what’s common across firms of all shapes and sizes is that AI’s potential remains largely just that — potential.
In my experience, firms are failing to unlock AI because of one or more of these reasons:
No one built the playbooks. AI needs best practice to amplify. That means the hard engagement-heavy work of codifying how opportunities are identified, pursued, and closed — practice by practice — as you get partners to commit to agreed ways of working. Most firms skip this or never think of it. So, there’s nothing to standardise, nothing to automate, and nothing to enable. Every Partner keeps doing things their own way.
The data lake is coming. It’s always coming. Just after the practice management upgrade. And the finance migration. And the security compliance project. Marketing and BD aren’t exactly first in the queue. And by the time they are, the promised lake is a polluted puddle. There’s a sad revert to spreadsheets and months of lost progress. These projects don’t really fail, they just never actually start.
Rubbish data. More than 4 in 10 firms have no CRM.* Others have one that’s a poor cousin to practice management software — which is fuelled by billing-focused data that’s woefully thin on relationships and anything marketable. The rest have data scattered across Outlook, unmanaged spreadsheets, and the memory of a handful of human knowledge oracles. Very few firm have robust segmentation for work types, industries, or client tiers. So, when you feed AI rubbish you get rubbish back — just faster, and with psychotic confidence.
Teams are set up for support, not for change. In many firms, BD and marketing are reactive functions who produce proposals, crank out content, and run events. They’re not embedded in the business as collaborators, coaches, or advisers working alongside partners to win work. And you can’t drive operational change without that mandate and proximity. As a result, AI ends up solving theoretical problems with zero practical impact.
Too much focus on the LLM. Not enough on automation. Many firms are treating industry-focused LLMs as their primary (almost exclusive) AI solution. Far fewer are mapping the full picture — client journeys, engagement triggers, briefing questions, frameworks, workflows, approvals, and insight capture. Everyone wants prompt-generated outputs, but the real value is in orchestrating the workflows and data around them.
Buying a product isn’t a strategy. When the hard work feels too hard, firms reach for off-the-shelf agents and quick-fix solutions. There’s merit in that if you can’t build internally or don’t want to. But it’s not a shortcut to the underlying problems. For marketing and BD teams – there’s still rubbish data. There’s no playbooks. There’s no buy-in for change. Buying an agent doesn’t build agreed ways of working, it just hands the workflow problem to someone solving it on their terms. And it typically adds another technology to an already bloated stack.
The firms getting the most from AI aren’t looking for sexy.
They’re the ones getting ugly.
*Data from Camojee’s survey of 202 professional services firms — Rethinking Rainmakers report.
