Aipedia: Patent and trade mark attorneys
AI portfolio tools can score thousands of patents and trade marks for value and relevance, but their output depends on the data behind them. Advice to drop a right, or a valuation used in a deal, can lead to a claim if the data was wrong.
Part of: AI in patent and trade mark attorneys
In short
Attorneys and IP managers use AI to score portfolios, recommend which rights to keep or abandon, benchmark against competitors and support valuations for transactions, licensing and funding. CITMA's 2025 report flags that portfolio analysis depends on data quality. Errors include abandoning a right a client later needs, and valuations that overstate or understate rights relied on by investors or buyers. IPReg's AI guidance relies on existing duties. PI usually responds to negligence claims, subject to the policy terms, but valuation work should be declared to insurers.
Portfolio analytics tools score rights on factors such as citations, family size, remaining term, claim breadth and overlap with competitors' products. They help clients decide which rights to renew, sell, license or let lapse, and they support valuations used in mergers, acquisitions, licensing negotiations and funding rounds. For large portfolios, the cost savings from pruning can be significant, and AI makes the analysis fast.
CITMA's report on AI's impact on IP practice (July 2025) says portfolio analysis depends on data quality, and that AI output must always get human review.
The tools also know nothing the data does not show. A right may matter because of a product still in development, a licence under negotiation or a competitor's known plans. Only the client can supply that context, and the attorney has to ask for it.
Illustrative scenario: a firm uses an AI tool to recommend pruning a client's portfolio, and the client lets a group of patents lapse on that advice. Two years later a competitor launches a product that one of the lapsed patents would have covered. The client claims the lost licensing value, arguing that the firm relied on the score without asking about its product plans.
A related risk is due diligence on someone else's portfolio for a buyer, where missed defects in title or status can lead to claims if the deal goes ahead. See AI freedom-to-operate opinions.
A negligence claim over pruning advice or portfolio due diligence would usually fall within IPReg-compliant PI, subject to the policy terms. Valuation work is different: some insurers may treat it as a distinct activity, so check it is declared and within the scope of your professional services. Claims involving transactions or funding can be large and may involve third parties who relied on your work, which raises questions of duty of care and of how your limit and aggregation apply. Under the duty of fair presentation, tell insurers about valuation and transaction work. See duty of care and top-up cover.
Apex arranges PI for patent and trade mark attorneys, and a broker can check that portfolio and valuation work is declared and covered. See the attorneys hub and AI docketing and renewals.
A score can inform the advice but should not be the advice. Check the underlying data, ask the client about product and licensing plans, explain the basis and limits, and get written instructions before any right is dropped.
It may, subject to the policy terms and what you have declared. Some insurers may treat valuation as a distinct activity. Check it falls within your described professional services, and tell insurers about valuation and transaction work under the duty of fair presentation.
To the client, usually the attorney who gave the advice, because the duty is to advise competently whatever tools are used. The firm may have rights against the vendor, depending on the contract, which is why CITMA's procurement guidance on liability terms is useful.
CITMA's July 2025 report on AI's impact on IP practice flagged that portfolio analysis depends on data quality, and said AI output must always get human review. It did not address insurance.
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