Throughout this week, we’ll be running an ‘In Focus’ series revolving around AI in the insurance and protection space, we’ll be exploring how artificial intelligence is shaping the future of the sector. With AI discussions taking centre stage, we’ll hear from a range of experts sharing practical insights, real-world examples, and guidance on implementing AI safely and effectively.
In the following piece, Cameron Erskine, wealth management consultant and financial adviser at SeventySeven Wealth Management, cuts through the hype to examine where AI is already adding real value, and how professionals can adopt it responsibly and with confidence.
In today’s climate, the question is no longer whether protection firms should engage with AI, but how to implement it in a way that is practical, commercial, and regulatorily robust. It’s challenging to ignore the hype and cut through the buzzword phrases to uncover practical and safe applications which genuinely improve outcomes. Our industry is built on trust and accountability. Experimentation without oversight is not innovation; it is unnecessary risk. When implemented thoughtfully, AI can enhance our processes and outcomes.
So, where is AI already helping firms? Firstly, and arguably most importantly, is in the advice process. AI is a powerful copywriting tool and can draft suitability reports, write letters, and organise client communications, transforming jargon into client-friendly language. AI has also been implemented into client meetings, transcribing conversations and summarising them into digestible notes. These administrative uses may sound bland, but can recover many hours each week across teams, allowing for more time for clients.
Many firms are also utilising AI for research and technical support, with accurate, consistent knowledge and fast processing, all available at your fingertips. Lengthy provider literature can be instantly analysed and summarised with key points, and comparisons pulled out, providing time and energy savings at scale. Technical knowledge could be regularly updated on a secure, centrally managed database, with the ability to quickly understand new topics and prepare for meetings in record times.
Outside of the advice process and client meetings, AI also delivers value to businesses through operational support. Utilising AI as a business consultant allows for process mapping and optimisation, leading to cost savings across a business. There is further value in performance analytics through detailed analysis of call recordings. Compliance requirements can be monitored, as well as the delivery of recommendations and the identification of further client engagement opportunities, enhancing managerial reviews.
Identifying the right tools and implementing them into your business effectively is the next step. Firstly, contact your network or service providers. They will most likely have a list of approved tools and services which can be easily integrated into your workflows and pre-existing systems. In these cases, the time and research required can be significantly reduced, but due diligence is still essential. Next, speak to your colleagues and nearby firms. Most other firms are asking the same questions as you; some may even have the answers you are looking for.
These tools and services are seldom without cost; some can even come with a larger-than-imagined subscription cost. However, when considering the cost of the tool you are looking at, compare it to an employee. Consider how much it may cost your business to hire someone to complete these same tasks – viewing AI tools as another employee can bring the cost into a realistic perspective. Will these tools replace your staff members? No. But they will dramatically increase the efficiency of your teams, allowing you to undertake a higher volume of work.
It’s key to remember that we’re dealing with confidential client data here. Having Data Protection Impact Assessments (DPIAs) and internal AI policies can help to protect your business and your clients’ data. AI does not replace humans – having human oversight of these systems is essential to your operation. It’s critical to avoid consumer-grade accounts on standard chat interface models like ChatGPT, Grok, DeepSeek, Kimi, or Claude – the input/output data is not always end-to-end encrypted, leaving client data vulnerable. Complying with data handling standards for client information must be a priority. Some of these models offer business/enterprise-grade deployments; if you’re interested in using these types of models, make sure to research data-safe options.
Making safe decisions as you adopt AI is non-negotiable. Being disciplined, careful, and thorough in your implementation will set the scene for the future of your business. Firms that ignore AI risk are falling behind operationally and competitively. AI will not redefine our values, but it may redefine how efficiently we deliver them.
