How Knowledge Agents Will Change the Way AEC Firms Scale Expertise and Accelerate Learning

Imagine you’re early in your career and newly staffed on a healthcare project. You’ve been asked to help work through the onstage/offstage model for a new facility—a concept you’ve heard before, but you don’t feel fluent enough in to start designing with confidence. You know your firm has done this work many times, and you know the knowledge exists somewhere. What you don’t know is where to look or how to get started.

So you turn to your firm’s AI-powered Healthcare Knowledge Agent.

You ask a simple, situational question: What are the key considerations when designing an effective onstage/offstage model for a healthcare project? The response you get is grounded in how your firm approaches healthcare work. It draws from internal best practices, past projects, and recorded talks from senior healthcare leaders. It highlights what to pay attention to early, where teams often run into trouble, and how different decisions affect patient experience and staff workflows.

Along the way, it points you to specific internal resources—an upskilling video on healthcare planning, linked directly to the exact moment where this concept is discussed; a standards page that captures onstage/offstage best practices; and a case study from a past project that shows how these ideas come together in the real world. If you want to go deeper, you can. If you just need enough context to start shaping a design direction, you have it.

Later that week, you’re asked to begin contributing to an imaging suite—something you’ve never worked on before. You ask the Healthcare Knowledge Agent what’s important to consider. Again, the agent synthesizes the firm’s best thinking, pulling together insights from different people, in different formats, shared at different times. And when follow-up questions move into territory it can’t answer with confidence, it doesn’t pretend otherwise. It clearly signals the limits of its knowledge and points you to the right subject-matter experts to answer the hard questions.

You’re able to stay in the flow of work—learning as you go, making progress, and building confidence.

Now imagine the same moment from the other side of the equation.

You’re one of the firm’s healthcare leaders. You’ve spent years building deep expertise through projects, research, and mentoring. You care deeply about developing the next generation, but you also know how often your time is consumed by answering the same foundational questions—important questions, but repeatable ones. Questions that interrupt deep work and pull you away from clients, strategy, and the harder problems that really need your attention.

By contributing to your firm’s digital knowledge base—through interviews, recorded talks, and curated guidance—your expertise becomes accessible on demand, 24/7, in a form that’s contextual, searchable, and connected. When emerging professionals come to you with questions, they’re better informed and more specific. Your time is spent mentoring at the right level, serving clients, advancing the firm’s thinking, and continuing to add new insights that strengthen the firm’s collective knowledge over time.

In short, your expertise has been leveraged so you can have more impact and your firm’s emerging professionals can develop faster.

Once you can imagine this working in healthcare, it’s not hard to extrapolate the same pattern applying elsewhere—whether that’s a Sustainability Knowledge Agent helping teams navigate materials and approaches, or a Revit Knowledge Agent supporting designers while freeing design technology teams to focus on innovation. Across disciplines, the dynamic is the same: expertise scales, learning accelerates, and the organization gets smarter.

This vision explains why Knowledge Agents will be the next major pillar in the Synthesis platform, alongside Intranet, LMS, and AI Search capabilities.

In this issue of Smarter by Design, I’ll take you deeper into how Knowledge Agents will work, what processes and cultural habits will make them successful, and how you can begin to lay the foundation for their arrival later in 2026.

Why Knowledge Agents Now?

In the fall of 2024, we released Synthesis AI Search into beta with our community. The uptake was immediate and right away we noticed that our clients were using it in ways that went well beyond what we originally imagined for a firmwide search tool.

We received feedback through every channel available to us: in-product ratings, client success conversations, community meetings, and one-on-one discussions. And as we started reviewing how people were actually working with AI Search, a clear pattern emerged.

Firms weren’t just asking broad questions across their entire knowledge base. They were trying to use AI Search to draft proposal answers, write blog posts, answer support tickets, create lesson plans based on videos, and more.

They were effectively trying to turn a general-purpose search experience into something that could act like an AI assistant—one that understood a specific domain, a specific audience, and a specific job to be done.

In other words, people were pushing AI Search to its edges.

That behavior was telling. In product design, when users are willing to work around the friction which accompanies using a tool for something other than its intended purpose, they’re usually pointing you toward something valuable that doesn’t exist yet. AI Search was getting them closer than anything they’d had before. But it wasn’t quite the thing they were reaching for.

What became clear is that AEC firms need two different things:

1. Firmwide AI Search: a powerful, natural-language way to explore everything the organization knows, across documents, pages, videos, and conversations. 

2. Knowledge Agents: purpose-built, use-case-driven AI assistants grounded in a specific subset of the firm’s knowledge and designed to help people accomplish a particular goal.

Synthesis Knowledge Agents won’t be a replacement for AI Search. They’ll be a complement to it. They’ll build on the same underlying capabilities—natural language understanding, synthesis across formats, citations, feedback, and epistemic humilty—but package those capabilities into a more focused form. Instead of asking a general system to be everything at once, a Knowledge Agent will be designed to do one thing well: support a specific workflow, discipline, or role.

Some Knowledge Agents will be personal, created by individuals to support how they work. Others will be shared across a team, department, or discipline. And some will be firmwide—available to everyone as a trusted starting point for a particular kind of work.

What they all share is the same design philosophy: they’re grounded in firm knowledge, they’re clear about their boundaries, and they’re designed to know when to help and when to hand things off to a human instead.

Knowledge Agents as Digital Ambassadors for Expertise 

When we first started talking about this next phase of AI-powered knowledge management, I often used the metaphor of digital twins. In AEC, it’s a familiar concept. We build digital twins of buildings and infrastructure all the time, so the idea of creating a digital twin of an expert’s knowledge felt intuitive — even a little playful. It usually landed well in presentations.

But over time, that metaphor started to feel wrong.

A Knowledge Agent will never be a true digital twin of a human being or a team of human beings. It can’t replicate their lived experience, passion, intuition, judgment, or creativity. 

I think a better way to think about Knowledge Agents is as digital ambassadors for your firm.

A digital ambassador represents expertise, but within clear and intentional boundaries. It speaks on behalf of the firm’s accumulated knowledge in a particular domain — healthcare planning, sustainability, Revit standards, marketing communications. 

A well-designed Knowledge Agent handles the routine, foundational, and repeatable. It answers the 101 and 201–level questions that come up again and again. It helps emerging professionals get oriented, understand terminology, and make informed early decisions. It dynamically pulls together the firm’s best thinking from guides, videos, courses, and past work, and presents it in a way that’s situational, contextual, and grounded for a special question from a special person.

Just as importantly, a good Knowledge Agent knows the limits of its knowledge. In those moments, its job is to say “I don’t know,” and route you to the right next step.

That might mean pointing you to a specific subject-matter expert whose judgment matters in that situation. It might mean recommending a deeper resource from your firm’s knowledge base. It might mean suggesting a relevant training or course to build more context before proceeding.

That epistemic humility isn’t a limitation — it’s a design feature.

Scaling Expertise and Accelerating Learning with Knowledge Agents

I don’t think we should strive for Knowledge Agents to replace human expertise. They should help AEC firms scale expertise and develop talent more effectively.

They should enable emerging professionals and other team members to make progress at their own pace and on their own schedules. And they should allow experts to spend more time on mentoring, client work, research, and advancing the firm’s thinking — rather than answering the same foundational questions over and over again.

This matters even more when you look at how the next generation of AEC professionals wants to work. Many are deeply self-directed. They’re accustomed to learning on demand, assembling context for themselves, and making progress without waiting for permission or perfect handoffs. They don’t want to bypass mentorship, but they also don’t want every question to require a conversation.

Knowledge Agents are built for that reality. They give people a way to orient themselves, research solutions, and build confidence independently before escalating. They support curiosity without friction. And over time, they make it possible for individuals and teams to shape how they access knowledge — effectively assembling their own assistants to help guide work in ways that match how they think and operate.

From a learner’s perspective, this changes how development happens. Learning becomes more personalized, more continuous, more contextual, and more closely tied to real work. People can stay in the flow, build confidence faster, and arrive at conversations with experts better prepared.

From an organizational perspective, something even more important happens. Knowledge Agents create a powerful opportunity to connect people to the right knowledge or expert at the right time because they sit at the intersection of intranet content, learning programs, and AI-powered retrieval.

Knowledge Agents are not magic. They’re not omniscient. And they’re not meant to stand alone. They’re designed to work as part of a broader knowledge ecosystem alongside firmwide AI Search, a robust digital knowledge foundation, curated learning experiences, and human relationships.

What It Will Take to Succeed in the Knowledge Agent Era

I want to talk about what it will actually take for Knowledge Agents to succeed — not technically, but organizationally. The firms that get the most value from this next era will be the ones that invest in the foundations, habits, and feedback loops that make knowledge usable in the first place.

There’s a line in The Living Company by Arie de Geus that I’ve carried with me for years. In his study of organizations that managed to survive and adapt for centuries, de Geus argued that “the only sustainable competitive advantage in business is the ability to learn faster than your competitors.”

That idea feels more relevant than ever in the AI era.

Knowledge Agents won’t create competitive advantage on their own. They’ll amplify it. They’ll reward firms that already take organizational learning seriously, while giving firms beginning their knowledge and learning management journey a clearer path to become smarter, more resilient, and more sustainable over time.

In practice, that success will show up through three commitments.

1. A sustained commitment to your digital knowledge foundation

Knowledge Agents will only be as effective as the knowledge they’re grounded in.

This sounds obvious, but it’s worth saying plainly: if the most important knowledge in your firm is outdated, fragmented, or hard to trust, no amount of AI layered on top will fix it. Knowledge Agents won’t replace the need for good knowledge management, but they will raise the ROI.

Succeeding in the Knowledge Agent era will require treating your digital knowledge foundation as a living system, not a one-time project. That means being deliberate about what knowledge actually matters, prioritizing its capture, keeping it current, and retiring what no longer reflects how the firm works today.

The value of having a solid digital knowledge foundation has already been shown with AI Search. AI Search has dramatically improved the ability to find and apply knowledge in context, raising the ROI of well-captured content that may have been underutilized.

Firms with solid digital knowledge foundations have already seen the benefits with AI Search. It has dramatically improved the ability to find and apply knowledge in context, raising the ROI of well-captured content that may have been underutilized.

Just as importantly, AI Search surfaced gaps where the firm’s knowledge was thin, outdated, or fragmented—and, in doing so, created a powerful incentive to fill them. When experts can see exactly where a better knowledge foundation would make their work easier, faster, and more effective, high-quality contributions start to flow. In that way, AI Search has acted like a magnet for firmwide knowledge—pulling expertise into the system because the value of contributing is suddenly obvious.

Knowledge Agents will amplify that dynamic. The same standard, lesson, or project insight will be accessible via firmwide search, learning programs, and multiple use-case-specific Knowledge Agents at once.

And, once again, gaps will become visible. When a Knowledge Agent can answer many questions well but falters in specific areas, it will make the missing knowledge visible. For experts and leaders, that clarity will create a new incentive: a clear opportunity to invest time where it will have the greatest impact, strengthening the digital knowledge foundation, and improving outcomes across the firm.

2. A commitment to creating the conditions for expertise to scale

If Knowledge Agents are going to succeed, firms will need to make a clear and sustained commitment to how expert knowledge is transferred.

There are experts in every AEC firm who have accumulated years of experience through projects, client relationships, research, and hard-earned lessons. They are often generous with their time, but they are also busy. And asking them to simply “document more” has never been a realistic or effective strategy.

Succeeding in the Knowledge Agent era will require a different approach.

The firms that get this right will set a clear expectation: being a subject-matter expert isn’t only about solving client problems or mentoring one person at a time. It also means acting as a steward of the firm’s digital knowledge foundation—helping to externalize what you know so it can be shared, reused, and built upon.

But just as importantly, those firms will design systems that make that stewardship easier.

We’re already seeing strong examples of what this looks like in practice. At Shepley Bulfinch, for instance, the technology team partners directly with experts through structured interviews, captured on video. The burden of production—interviewing, editing, publishing, and packaging the content—sits with a dedicated team. The expert’s role is focused and respectful of their time: show up, share what you know, and review the result before it’s released.

At LS3P, the marketing and knowledge management teams have taken a similar approach through their Expert Hours program. They facilitate firmwide conversations with subject-matter experts—sometimes one-on-one, sometimes between peers—and then take responsibility for transforming those conversations into reusable knowledge assets. That content supports internal learning, external storytelling, and firmwide alignment, all without requiring experts to become full-time content creators.

These examples point to an important shift. This work can’t be accomplished by asking experts to just “share and document more” when their plates are already full. It requires putting programs, processes, and people in place to support knowledge transfer intentionally. Interviewers, editors, instructional designers, and knowledge and learning managers all play a role in turning lived experience into shared understanding.

3. A commitment to feedback and continuous improvement

The final commitment is what turns all of this into a living system.

Once Knowledge Agents are in use, every interaction becomes a signal. When someone rates an answer as unhelpful, asks a follow-up the agent can’t answer, or escalates to a human, it’s not a failure—it’s feedback.

Over time, those signals reveal where knowledge is missing, duplicated, conflicting, outdated, or unclear. They expose gaps in knowledge ownership. They surface assumptions that no longer hold. And when firms pay attention and act on that feedback, the system gets better—not just the agent, but the underlying digital knowledge foundation itself.

This is one of the most powerful, and often overlooked, aspects in knowledge management. Increasing the usage of your firm’s digital knowledge foundation improves it by making gaps, contradictions, and content priorities visible. The more the system is used, the clearer the firm’s thinking becomes. Learning accelerates because learning is designed into the workflow.

This is why we see Knowledge Agents not as a feature, but as part of a broader shift towards becoming more intentional about knowledge and learning management—a shift that many firms in our community are actively exploring. It’s also why so much of our work this year, including the conversations we’ll have at KA Connect 2026, is focused on what it really means to design modern learning organizations in the AI era.

So Where Do You Start?

Earlier, I mentioned that Knowledge Agents will become available to Knowledge Architecture clients later in 2026.

If this direction resonates, the question isn’t when to adopt them. It’s how to prepare now in a way that sets you up for success down the line.

I think the most useful place to start is with Jobs to Be Done.

What are the most important and recurring areas in your firm where knowledge—or access to expertise—is the bottleneck?

When you look through that lens, potential Knowledge Agents tend to reveal themselves quickly. Whether that job lives in healthcare planning, sustainability, design technology, onboarding, or operations, the pattern is the same: where expertise becomes a bottleneck, a well-designed Knowledge Agent can create leverage.

Once you can picture a specific agent, the next questions follow naturally.

• Who holds the expertise that the agent would need today?

• Is that knowledge concentrated in one person, a small group, or scattered unevenly across the firm?

• Would making this knowledge more accessible create leverage for experts while accelerating learning for others?

In practice, one of the simplest ways into this work is to talk with your experts and department leaders and ask a direct question: What do people ask you about over and over again?

Those repeat questions are signals. They point to places where better knowledge access could meaningfully change how work gets done.

From there, you can work backward to the digital knowledge foundation.

• Do you already have the guides, standards, best practices, or learning resources that Knowledge Agent would rely on?

• Is that knowledge clear and current—or duplicated, outdated, or missing entirely?

• What would need to be captured, updated, or archived to make that Knowledge Agent genuinely useful?

Answering those questions helps focus effort where it matters most: prioritizing use cases, interviewing experts, capturing tacit knowledge, creating learning assets, and assigning ownership so that knowledge stays alive over time.

Knowledge Agents will be here before you know it. The firms that benefit most won’t be the ones who rush at the end—they’ll be the ones who start now by identifying their highest-leverage Jobs to Be Done and preparing the knowledge those agents will depend on.

If you’re already working with Knowledge Architecture, this is a good moment to take advantage of our community events, shared resources, and Client Success team as you begin planning for Synthesis Knowledge Agents. And if you’re not a client—and this way of thinking resonates—we’d love to talk.

We’ll continue sharing what we’re learning here in the newsletter, on the Smarter by Design podcast, and across the KA Community. 

Stay tuned.