From my experience working with law firm marketing and business development teams, AI adoption often starts the same way. A team sees a tool demo and builds a short list of use cases. They imagine faster proposals, steadier thought leadership, sharper competitive intelligence, and fewer hours spent moving information between systems. Those goals make sense. But they all depend on one assumption that gets little attention: people already share information well enough for AI to use it.
Many law firms appear to be finding out that assumption doesn't hold. Lawyers and business professionals are adopting generative AI faster than firms are building the training, shared processes, and oversight needed to support it. AI then lands inside a workplace where marketing, business development, attorneys, and practice groups often hold different pieces of the same client story: different notes on history, different views of priorities, different memories of past work.
The software can only work with what people give it. It also carries forward every missing field, delayed approval, private spreadsheet, and unclear handoff into whatever it produces. Over the next year, I expect that gap to become harder for law firm leaders to ignore. AI use will keep growing, and the firms that gain a real edge will likely be the ones where marketing and business development already work as a single connected function rather than two separate departments trading files back and forth.
Usage Is Outpacing Firm Structure
Individual adoption has moved far ahead of firm structure. According to the American Bar Association's coverage of the 8am 2026 Legal Industry Report, personal generative AI use among legal professionals rose from 31% in 2025 to 69% in 2026. During that same stretch, 54% of respondents said their firms had given no training on responsible AI use and had no plans to start.
The concerns behind that training gap run deep. Respondents pointed to data security at 46%, ethical issues at 42%, privilege concerns at 39%, and a lack of trust in AI results at 39%. These numbers describe firms where use spreads through individual initiative while firmwide support stays thin.
That gap shapes how people judge AI's payoff. The Thomson Reuters Institute's 2026 Future of Professionals report found that 91% of surveyed professionals had felt some distance between what AI promised and what it delivered. More than a third used tools their own organizations hadn't approved.
For a law firm CMO, this creates a messy working environment. A marketing professional might use one tool to draft content. A BD professional might use another to prepare a pitch. The attorney might edit both without recording the changes or the client context behind them. Each person gets faster at their own task, while the firm's shared process stays fragmented underneath.
More activity can hide that fragmentation for a while. It can't remove it.
Strategy Gets Lost in Translation
Most firms now accept that AI needs some kind of strategy. The harder part is carrying that strategy into the work people actually do every day.
The Thomson Reuters Institute's 2026 Stand-out Lawyers Survey shows the distance between those two things clearly. Nearly 80% of stand-out lawyers believed their practice had a clear plan for AI integration. Fewer than half felt confident their practice area could actually succeed as AI became a bigger part of legal work. Only 25% strongly agreed their firm had a plan to turn AI use into real revenue.
That gap creates an odd kind of management problem. A firm can have an approved strategy, licensed tools, written policies, and training sessions, and still lack a shared way to move work between teams. The strategy stays stuck at the leadership level because nobody has translated it into decisions about who owns what, who provides the inputs, who reviews the output, and who follows up.
The same survey found that partners who used AI daily, across several kinds of work, were nine times more likely to report a real boost in efficiency and quality than partners who used it rarely. Simply having access to a tool explains very little on its own. Using it regularly, inside a repeatable process, seems to make the difference.
For marketing and BD leaders, turning AI into revenue depends on that same discipline. AI-generated work needs reliable client context, market data, experience records, brand guidance, attorney judgment, and an agreed next step. If ownership shifts at every stage of that chain, a firm's AI strategy will produce scattered pockets of efficiency instead of one connected commercial result.
Business Development Depends on Shared Memory
That translation problem becomes very real inside business development. Firms already hold huge amounts of useful information: past proposals, matter descriptions, client interviews, relationship notes, sector knowledge, attorney experience, event follow-ups, and the reasons behind old wins and losses. Much of it sits scattered across separate systems or individual files.
A Law.com article by Mike Mellor frames this as a memory problem rather than a selling problem. Knowledge the firm already possesses can become unavailable at the exact moment a lawyer or BD professional needs it most. An outdated experience record or a relationship note that never got written down can weaken a pitch long before AI even starts drafting anything.
AI can retrieve and organize stored information fast. But its value drops sharply when the underlying record lacks context, consistency, or basic access. An incomplete experience database produces incomplete evidence. A CRM full of stale relationship data produces weak client insight. Proposal files with no record of why a pitch was lost limit what the firm can actually learn from it.
That turns culture into something concrete and operational. Collaboration means being willing to record what happened, share what was learned, agree on shared definitions, and let another team use that information without a fight. The software sits downstream of those choices; it can't create them.
Firms with stronger shared memory may start to pull ahead of their peers. They can reuse past experience with more precision, connect attorney knowledge to market demand, and carry client feedback into the next campaign or pitch. Firms with fragmented memory will spend more time double-checking AI output, simply because the system never had the history it needed to produce something relevant.
The Marketing-BD Handoff Decides Value
Marketing and business development usually chase the same revenue goals from different starting points. Marketing builds visibility, produces content, studies audiences, and manages channels. BD turns firm knowledge and relationships into pursuits, proposals, cross-selling conversations, and new client opportunities. AI only connects those two efforts when information actually moves between the teams.
The Legal Marketing Association has flagged a related issue: law firm AI programs often center on legal service delivery, leaving marketing and BD sitting at the edge of the strategy. That position limits how far a firm can apply AI across the full client-development cycle.
Consider the handoff from thought leadership to business development. Marketing might use AI to spot a timely topic, organize attorney interviews, and shape a first draft. Whether that work pays off commercially depends on what happens next. BD needs to know which clients care about that issue, which relationships can support a conversation, and which practice leaders will follow up. Marketing then needs feedback from those conversations to sharpen its next content decision.
A single break anywhere in that chain reduces the value of the whole sequence. Content volume can rise while client engagement stays flat. Campaigns can launch faster while relationship intelligence stays locked inside one team. Proposal production can speed up while the lessons from wins and losses never make it back into future planning.
The next phase of legal marketing AI will likely put even more pressure on this handoff. CMOs may need to ask a few plain questions before that pressure builds: who provides the context, who reviews the output, who acts on it, and who records the result so the next person can use it. Those questions are about how people work together inside the firm, and no software purchase answers them on its own.
Two Paths Are Beginning to Diverge
The broader track record of digital transformation offers a reason for caution here. An MIT Sloan Management Review analysis cites a Gartner survey of more than 4,200 leaders in which only 48% of digital initiatives met or beat their targeted business outcomes. The same analysis cites a 2025 BCG survey in which 60% of respondents said their AI investments delivered little real value.
Law firms may split into two groups as AI use keeps expanding. One group will keep adding tools to existing workflows and measure raw activity: licenses purchased, prompts run, drafts produced, hours saved on individual tasks. The other group will connect AI use to shared information, clear ownership across teams, client response, and actual business outcomes.
The first group may still show efficiency gains on paper. Those gains could get hard to defend once leadership asks how the work actually contributed to revenue, stronger client relationships, or smarter market decisions. The second group will have a much easier time tracing activity through the full chain, from insight, to campaign, to conversation, to opportunity.
The people risk may grow alongside this split. Thomson Reuters found that nearly three in ten mid-career professionals would consider leaving within two years if AI failed to deliver the value they expected, with an estimated replacement cost of $232,000 per professional. Teams asked to adopt AI on top of already broken processes may end up carrying a heavier workload instead of a lighter one, absorbing one more interface, one more review step, and one more source of conflicting information.
By 2027, the difference between experimenting with AI and actually running on it may show up clearly in retention numbers, client experience, and how much anyone trusts the internal ROI claims.
Collaboration Changes the Economics
Right now, expectations sit far ahead of delivery. A Thomson Reuters Institute law firm action paper reports that 70% of law firm professionals expect productivity gains from AI. Only 6% believe most firms are actually delivering them. Half say they see their firm's AI strategy reflected in daily work.
That gap represents both a risk and an opportunity. For CMOs, the financial case for AI gets easier to defend once the measurement follows work across teams instead of stopping at one desk. Time saved on a single draft is one data point. A sharper account brief, a faster pursuit decision, a higher attorney participation rate, or better reuse of firm experience offers a much richer picture of what AI actually contributed.
Shared measurement changes the conversations happening inside the firm too. Marketing can connect its content decisions to client priorities. BD can send pursuit information back into campaign planning. Practice leaders can see where their own participation moves the needle. Leadership gets a view of the whole process instead of scattered production metrics from separate teams.
I expect the next serious AI conversations inside law firms to circle these operating questions rather than tool comparisons. What information enters the workflow, and who owns its quality? Where does marketing hand work over to BD, and what comes back from that conversation? Who records the result so the next person can find it?
Those questions sound less exciting than picking a firmwide platform. They reach deeper into how the firm actually runs. They're also what create the conditions for AI to contribute to real revenue conversations without weakening judgment, brand integrity, or client trust.
The Next Advantage Starts Inside
The firms that pull ahead over the next year may have fewer dramatic AI stories than people expect. Their progress will show up in dependable handoffs, current information, shared definitions, and clear ownership. Marketing will know what BD needs before a campaign even begins. BD will send client intelligence back before the next planning cycle starts. Attorneys will contribute context at defined points instead of getting pulled in for last-minute rescue work.
AI will make those exchanges faster and easier to reuse. It will also expose every single place where the exchange breaks down.
From my vantage point, that may become the real test for legal marketing leaders over the coming year. The strongest commercial gains will likely come from firms that can turn shared knowledge into coordinated action. Tool selection still matters. Culture decides how far that value actually travels.