The Knowledge Agent for SharePoint: for Knowledge Management & Innovation Leaders

Gabriel Karawani, Director & Co-Founder

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The Knowledge Agent for SharePoint is an exciting new tool, so should you consider this as part of your content and knowledge management strategy?

Microsoft has recently introduced the Knowledge Agent in SharePoint (in preview as of September 2025), a new Microsoft 365 Copilot for SharePoint capability that brings some structured information management capabilities directly into end-users’ hands. The feature makes it possible to automatically generate columns, views, and rules that help organize content in document libraries.

For Knowledge Management and Innovation leaders, this shift is significant. Capabilities that were once hidden behind specialist expertise or IT governance are now moving closer to business teams and content owners. This democratization of metadata and structure is exciting, but it also raises questions about governance, consistency, and the role of KM leaders in guiding how these tools are adopted and scaled.

Defining knowledge management

At ClearPeople, the team behind Atlas, we often hear comments on how we are reimagining knowledge management. This is a great compliment and great for marketing purposes. In this article however, I think it is worth just to quickly clarify what I mean when I refer to knowledge management (KM) in its traditional form.

Simply speaking, KM is a process, which has the objective of capturing content that has or creates value when reused. Typically the KM process includes some variation of the following steps: Capture, Curate, Approve, Distribute, Review, Dispose. There are a number of slight variations of this process and the steps/step-names within it. In reality, they all amount to about the same thing and typically, they are shown as a circular process diagram of some sort.

Irrespective of the exact steps or shape of diagram, the takeaway is that KM is not a tool, a solution or a platform. It’s a process. You don’t buy “KM”, you buy tools, solutions or platforms that support the process of KM.

I venture that most real KMers out there, to lesser or greater degree, will agree with the above.

Where do knowledge management challenges typically lie

While I am conveniently going to ignore the perennial problem of “tacit knowledge” in KM, effective KM processing is hampered by a number of other challenges. Especially when working at scale in most organisations. Even small organisations will recognise a lot of these challenges.

I have revisited these challenges here, as they are important to consider in order to assess the potential impact, benefits and value of the Knowledge Agent in SharePoint as a solution or a tool for KM.

Step	Issue
Capture	Capturing information at the source or in the flow of work often does not happen.
Capture	End users forget where to correctly load content, resulting in files ending up in OneDrive or other incorrect libraries and folders.
Curate	People are often too busy, or find it too cumbersome and boring, to tag content properly.
Curate	Tagging is rarely done, and when it is, it is often incorrect or inconsistent.
Distribute	End users face information overload, mainly with irrelevant content.
Distribute	Permissions are often “over shared” to allow easier sharing.
Dispose	Multiple copies of content are rarely disposed of.
Dispose	Approved content becomes stale and outdated, and thus implicitly incorrect.

Has the Knowledge Agent turned SharePoint into a KM solution?

When testing and reviewing the Knowledge Agent’s capabilities, it is clear that this is a very useful tool in the making.

But as with all technology, there is a risk that marketing messaging and Microsoft-fan-posts lead to setting the wrong end-user expectations and that the shiny new tool effect quickly wears off. Some articles, for instance, have concluded that the Knowledge Agent turns SharePoint into a Knowledge Management solution.

Microsoft’s own getting started article (https://learn.microsoft.com/en-gb/sharepoint/knowledge-agent-get-started) sets the expectations quite well with this sentence: “Knowledge Agent is a built-in SharePoint capability designed to help your organization prepare content for AI.”

The subsequent sentence unfortunately does quite the opposite: “It enriches, organizes, and maintains SharePoint content in a structured, authoritative format—optimized for Microsoft 365 Copilot agents.”

To me, this sentence is not clear, and it is open to interpretation and counter arguments.

First, it implies that the agent looks across SharePoint to enrich content. It does not. It looks at a library at a time, which means that the enrichment does not take into account how similar content stored elsewhere may have been tagged.

Second, it assumes that the enriched output is an authoritative result. It is not. Unless you are willing to fully trust the suggested metadata as authoritative without validation or approval, which very few will.

Thirdly, it implies that *it* organizes and maintains content. It does not. It suggests actions to users (Owners and Members in the Site, List or Library) visiting that site, list or library who each – and independently of each other – decide whether they agree with the Knowledge Agent’s suggestions.

I get it and it is a very exciting time to work in the crosshairs of tech and knowledge management, but I am super-keen to make sure we leverage the new tools for the job(s) they are meant for.

I know that experienced knowledge management leaders will quickly see through the marketing hype, and like me, will also get excited about the actual opportunities that the Knowledge Agent does in fact bring to the knowledge management solution toolbox.

So, no, turning on Knowledge Agent for SharePoint, does not turn your SharePoint into a Knowledge Management solution. It does however offer tooling to solve discreet problems within information silos, which in turn can help the overall knowledge management process outcomes.

Evaluating Knowledge Agent in SharePoint

We can break down the high-level features and preview actions in the Knowledge Agent as follows below.

REMINDER: The Knowledge Agent works within the silo of the current Site or Library the user is in.

Site Pages

Fix broken links

Retire inactive pages

Find content gaps

Create and publish pages from site content

Create an FAQ (based on static page content)

Summarize this page (based on static page content)

Libraries

“Organize library “

- Create columns

- Create a rule

- Extract key actions

- Summarize documents

“Create rules”

“Create new view”

Lists

Not currently supported in preview.

I am not going to describe the features above in any further detail here, as Microsoft’s own materials do a decent job of that. Also, keep in mind that each of these features above in reality are “prompts” to the Knowledge Agent, meaning you can of course ask the agent to assist with something else.

Instead, let’s consider each of these features/actions above from a knowledge management process perspective.

Step	Issue	How can Knowledge Agent help	Score
Capture	Capturing information at the source or in the flow of work often does not happen.	Knowledge Agent does not specifically address this.	0/5
Capture	End users forget where to correctly load content, resulting in files ending up in OneDrive or other incorrect libraries and folders.	Knowledge Agent does not address this and non-SharePoint locations (including OneDrive) obviously do not support SharePoint metadata.	0/5
Curate	People are often too busy, or find it too cumbersome and boring, to tag content properly.	Here, the Knowledge Agent can really shine, with auto-filling of metadata within document libraries.	3/5
Curate	Tagging is rarely done, and when it is, it is often incorrect or inconsistent.	Knowledge Agent will attempt to tag in many cases, but naturally you need to expect that the tags may be incorrect and so will require review. Especially for taxonomy based Managed Metadata data.	2/5
Distribute	End users face information overload, mainly with irrelevant content.	In combination with search interfaces, the Knowledge Agent’s enhancement of content through tagging, will offer more opportunities to deliver relevant and search results. Subject to the metadata being reasonably correct.	2/5
Distribute	Permissions are often “over shared” to allow easier sharing.	Knowledge Agent does not address this.	0/5
Dispose	Multiple copies of content are rarely disposed of.	Knowledge Agent can potentially assist in identifying duplicates within a single library. It cannot do this across multiple libraries (or multiple sites).	1/5
Dispose	Approved content becomes stale and outdated, and thus implicitly incorrect.	Page reviews: Currently Knowledge Agent appears to be handling this decently for pages in a site (possibly due to available analytics).	3/5
		Document review: prompting the agent to identify outdated or stale documents (in various variations of the prompt) only resulted in a suggestion to create a (new) column to track modified date (which is already a column).	1/5

My scores are obviously completely arbitrary, based on limited testing and I recognize that Knowledge Agent for SharePoint is in preview. So naturally, I am happy to take feedback for further review.

From the table, I want to call out the two excellent features that both score 3/5:

Auto-filling: despite lots of teething issues (and nasty defaults being set for auto-generated columns) this is where the real power of the Knowledge Agent comes to the fore and shows a great potential. The score of 3/5 may be a bit generous at this stage, but the opportunity here is fantastic as the capability matures. It will however be vital to appreciate how to manage and deploy this capability at scale in enterprise scenarios. (Note that the quality of the tags themselves score 2/5.)
Page reviews: I feel like this capability might stretch to a 4/5 as the initial testing looked really good and pretty well baked. It will need proper testing on larger sets of real site pages with good content, a decent user base and comparable usage statistics to validate degree of false (positives/negatives).

I also want to highlight the most disappointing outcome: Why has Microsoft not doubled down on one of the most common admin problems for content managers: Duplication of content. Considering that the scope of the Knowledge Agent is restricted to the silo of a library, having a simple pre-canned and optimized tool the agent can call to check for duplicates - within that library - seems like a huge miss.

Risks associated with leveraging the Knowledge Agent and the Metadata Silo

Ignoring any risks related to leveraging preview or maturing technology, let me highlight some key concerns I raised in my earlier blog (here). Naturally, we expect that some of these may improve as the Knowledge Agent matures to General Availability and beyond. So, as of today:

There is no strong control over column naming conventions. Site members can accept suggestions; there are few (if any) constraints at the moment over enforcing naming standards.
Column creation via Knowledge Agent appears to create columns within the default content type. This may not align with custom content types or existing taxonomy.
Versioning: when metadata autofill is applied or updated, changes occur in current item version. There is no rollback option. So, if metadata is “over-enriched” or mis-applied, it may not be an easy undo.
Auditability is limited: it will be hard to trace who accepted what suggestion, when a column is added, or when metadata is filled in, especially if many site owners/members do this independently of each other.
There are a number of limits to metadata features: e.g. managed metadata term sets are only partially supported (only the first N terms are considered) in current version. That can limit accuracy and consistency if term sets are large.

As a consequence, a number of risks materialize. I have listed out the most obvious, but in reality, many of these boil down to a new type of information silo being created: The “Metadata Silo”.

Risk	Description	Consequences
Divergent column names (naming inconsistency)	If different site teams accept suggestions or create new metadata columns in their libraries, those columns may have different names, spellings, casing, punctuation etc. E.g. “ClientName”, “Client Name”, “Customer Name”, “client_name” etc. Also, display name vs internal name mismatches.	Problems for search and discoverability across sites; users may not find content if they search under different names. Difficult to build reports, dashboards, policies that assume standard metadata fields. Higher support / maintenance cost. Potential for duplicate or redundant metadata fields.
Inconsistent data types, formats, or column settings	Even where naming is similar, different libraries might have columns of different types (single line text vs choice vs managed metadata vs date etc.), different default values or different validation.	Inconsistent filtering, sorting, grouping in views; broken or non-uniform behavior; poor user experience; difficulty in applying enterprise rules; risk of data integrity issues (e.g. date formats or locale issues).
Overlapping / redundant metadata fields	Multiple fields might cover overlapping concepts, but people don’t know which to use; e.g. “Department” vs “Dept”; “Project Code” vs “Proj Code”. With the Knowledge Agent suggesting new columns “on the fly”, redundant fields are likely.	Confusion for content creators/users; metadata fragmentation; inconsistent tagging; drift in how fields are used; difficulty aggregating or integrating metadata; duplication of effort.
Inconsistent tagging / classification	Similar content might be tagged differently across sites, or tags might use free text vs controlled vocabulary vs managed metadata vs no standard taxonomy. Some content may not get tagged properly or gets mis-tagged due to AI misclassification.	Poor search or Copilot responses (which rely on metadata for “grounding”); difficulty in running enterprise reporting; compliance risks (e.g. regulatory or records management) if classification or retention policies rely on metadata; risk of data silos.
Unexpected overwrites / “drift” over time	Autofill or metadata autofill may overwrite existing metadata (if run automatically) or change behaviour when content changes. Also, when column suggestions are revised, new versions of content may diverge.	Loss of previously entered metadata; inconsistencies between content versions; confusion when the same document looks different in different contexts; potential audit issues; user distrust if metadata changes without clear visibility.
Lack of governance / oversight	As noted in early commentary, Knowledge Agent gives site owners and members power to create columns, accept suggestions, set up views / rules etc., often with limited controls (e.g. little or no control over column naming, limited audit trails) in preview.	Potential for inconsistent practices, accidental non-alignment with enterprise architecture or taxonomy, difficulty enforcing compliance, higher risk of information chaos rather than order.
Scalability complexity and coordination issues	In large organizations, many sites, many authors, many kinds of content. Without central coordination, what works in one site may not in another, and the number of metadata fields and variations may explode.	Search, discoverability, knowledge management degrade; user confusion; technical debt in metadata; burden on governance teams later; risk of rework or migration costs.
Localization / multilingual inconsistency	If metadata display names or column labels are in different languages, or formats differ by locale, this might further complicate consistency across global sites.	Users in different regions may misinterpret, search fails; duplication of metadata fields; inconsistent filtering or translation issues.

Leveraging the Knowledge Agent for SharePoint in enterprise scenarios

Irrespective of all the concerns and the risks, the fact remains that the Knowledge Agent is on track to become a very powerful tool in the right hands and when employed sensibly.

Whether you are a local, regional or global law firm, a small or large professional services business or a global multinational multidisciplinary firm of professionals, you will be dealing with “enterprise scenarios”.

Real world business is not confined to single SharePoint sites or libraries, and as knowledge management leader it is vital that your information architecture, your taxonomy and your filing experiences are as easy and consistent as possible. This is what gives you a fighting chance to deliver great output.

So, how might you consider leveraging the Knowledge Agent within your content or knowledge management platform design?

This is clearly a topic which is rich enough for a separate article, but let me highlight a few key pointers:

The more autonomous / free-will your front-of-house is, the more you need rigor and discipline in the backend to avoid tagging chaos, metadata silos and unintended loss of context.

In other words, you will need a solid enterprise-wide approach that includes:

Taxonomy management, offering clarity while being flexible to change
Provisioning of Teams and Sites, while being business centric
Template based governance (from site down to lists and library/folder level)
Self-service approach to “bring people in”, rather than going rogue with various agents.
Implement simple and speedy approaches to approvals where possible
Create an accountability framework and “safe spaces” to share mistakes or mishaps.

Closing thoughts

As with most other tools, the Knowledge Agent for SharePoint is not a silver bullet for knowledge management, but it does represent an important evolution in how AI can support KM processes.

For Knowledge Management and Innovation leaders, the real opportunity lies in shaping how these emerging tools are governed and integrated into enterprise knowledge strategies.

Used wisely, the Knowledge Agent can play a role to reduce friction in curation, improve findability, and support better content hygiene. Left unmanaged, it risks creating metadata silos and increasing complexity.

KM leaders who start experimenting now, with governance guardrails in place and the right enterprise-wise platform architecture in place, will be better positioned to shape, rather than chase, how AI transforms enterprise knowledge practices.

The challenge, and the opportunity, for KM leaders is to strike the right balance between enabling business users and safeguarding enterprise-wide consistency. Those who do will not only harness the potential of the Knowledge Agent, but will also strengthen the role of KM as a driver of innovation and productivity.