Best practices for preventing legal risks and the role of AI

What are the major pain points that you have experienced as GC when dealing with legal disputes?
Dealing with claims against an organisation is a huge drain on resources for any team. Linking to the 80:20 principle, you don’t want to be devoting 80% of your resources to firefighting something that may be worth less than 20% of the legal team’s value to the organisation. Most legal teams want to be working proactively, helping the organisations they work within to grow by doing good business, not always picking up the pieces and firefighting after something has gone wrong. Reactive defence is incredibly time consuming and can involve significant numbers of people. Even if you have a team big enough to manage disputes in-house, few in-house counsel have much or any hands-on experience of litigation (and fewer have experience of ADR) beyond a seat in their training contract. Many in-house counsel also find disputes demoralising and a lose-lose situation for the legal team, if not also for the organisation. Therefore typically, dispute resolution is outsourced to external counsel once it escalates, because of the manpower and expertise available. Obviously, this comes at a cost which can be a sizeable chunk of the legal budget. Trying to make provision for disputes in the team’s budget typically involves quite a bit of crystal ball gazing. And the in-house team still has to be involved anyway. It’s no wonder that many tools have been developed to assist teams with case management, case strategy and paperless disputes.

How can in-house legal teams be more proactive in legal risk prevention and assessment?
All these pain points mean the legal team is usually striving to help the organisation avoid disputes in the first place. Clear contract drafting helps to avoid uncertainty, which can result in expectations unable to be met. Good dispute resolution clauses and mechanisms such as SLAs can give the parties a framework to help them manage a souring contractual relationship before it is irretrievably spoiled.

Spotting issues and taking early action often means smaller, less significant steps can prevent more painful experiences later on. Legal and/or PR teams can help customer relationship teams to develop responses that don’t necessarily admit liability, but leave customers satisfied that concerns have been understood and resolved appropriately. Keeping on top of legal and regulatory developments and updating the organisation on the risk of conflict with stakeholders is a critical activity for many teams, but in itself can be time consuming, requires expertise and it can be easy to miss the significance of a ‘small’ shift. In all cases, it’s crucial that someone connected with the day-to-day operations spots the early warning signs of an issue brewing and has someone to turn to for guidance if they aren’t confident in navigating an emerging dispute. Many legal teams are finding they can use technology to help spot these small shifts that can have large consequences.

What role can new technologies such as AI and predictive analytics play to support GCs in this domain?
Even lawyers and contract managers are human and sometimes wording is less clear than it could be or (gasp) erroneous. Not every customer, supplier or other stakeholder picks up the phone to politely explain their displeasure with a faulty whatsit, a service that wasn’t as expected or something that’s been niggling them. And not every niggle merits legal team attention. Thankfully, technology allows us to identify and analyse large amounts of small pieces of data, that on their own, may not be spotted or seem insignificant.

“Most legal teams want to be working proactively, not always picking up the pieces and firefighting after something has gone wrong.” Emma Sharpe

AI tools like Deriskly can show us trends and flag anomalies, enabling us to address them before they cause a kerfuffle. They can predict what will happen next if niggles mentioned on social media are not satisfactorily addressed, so we can set thresholds for action and pre-empt escalation. Natural language processing is getting better all the time. Much like a 12 year old trying to learn French, tools understand better than they ‘speak’, so while you may be fed up of strange responses from customer service chatbots, contract analysis tools can find and flag unintended inconsistencies in your contracts with relative ease.

What are the opportunities and challenges in adopting such technologies? How can the challenges be overcome?

  • Efficiency – tools can crunch through vast amounts of data in a fraction of the time it takes an experienced lawyer. Presenting data in digestible forms allows other teams, with repeatable guidance from legal, to handle matters otherwise handed over to the legal team for ‘expert attention’.
  • Effectiveness – tackling issues early on can avoid escalation into the kind of problem which brings greater risk and requires more time consuming, focused and expensive attention later.
  • Accuracy – AI tools can follow objective rules rather than succumbing to human behavioural biases.
  • Happier legal teams, preventing significant disputes rather than damage limitation after the event.


  • Cost – can be difficult to demonstrate ROI. Technology providers should be able to help build a business case with demonstrable ROI data from previous customers.
  • Change management. If the technology is implemented by the provider or a partner, they should help to map a change management process with FAQs, communications guides about what to expect, how to deal with issues/flag improvement opportunities, using ambassadors to ensure buy-in and drive adoption, phasing out old processes/technology etc.
  • Reluctance/inertia – educate and demonstrate benefits to legal teams and other stakeholders. Small pilot, narrow use case, for cheap/free, followed by wider roll out.

Emma Sharpe runs a consultancy business which helps c-suite, senior leadership and legal teams with different aspects of strategy, especially legal, governance, technology/process improvement and sustainable business. She has been a practising commercial lawyer for nearly 22 years, with 11 years in-house (twice at the GC level for large multinational corporates) and nine years in private practice with an international firm. She has experience in a variety of sectors including FMCG, outsourced services, international trade, shipping, logistics, defence and pharma.


Deriskly is an advanced AI analytics tool that helps in-house legal teams detect, analyse, and mitigate business risks from diverse data sources. Founded by a team of lawyers and computer scientists from the University of Oxford, Deriskly was named one of the five pioneers in the inaugural LawtechUK Sandbox in 2020-2021.

To learn more about how AI tools can help your organisation prevent and mitigate legal risks in real-time, visit