By Stu Breyer, CEO of Mallowstreet
Artificial intelligence (AI) has been part of consumers’ lives for years. Think about the recommendations Spotify serves up, or the ‘consider adding this’ prompt in your Amazon shopping basket. All of this is powered by data analysis and AI.
But now suddenly – and seemingly from nowhere – AI has arrived on the business stage.
Both personally and professionally, the one thing people constantly say they need more of is time. So when you are thinking about what AI tools to adopt in your business, it is important to work out what time efficiencies you are trying to solve and how you can measure the impact.
There are two broad approaches I have seen businesses take when it comes to AI. The first involves establishing so much bureaucracy that the ability to innovate becomes almost impossible. This red tape acts like an immune system, killing any potential to revolutionise a business.
The second scenario involves businesses creating an environment in which to trial AI tools, and a framework to evaluate their output.
Identify the use
I think every business needs a set of technology and AI adoption principles to help guide decision making. Wealth managers should embrace AI and trial new technologies to see what works for them to solve the immediate problems they face.
For example, AI could be used to write call reports, communicate with clients, create a social media and external engagement strategy, or become more efficient in the way we work internally and liaise as a team.
The list is endless. But the process should be simple: Find a problem and start applying solutions.
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Take meetings, for example. This is an area where I have seen wealth managers apply AI in a meaningful way. One company I recently spoke to had two back-to-back annual review meetings that were an hour long each. After the first meeting was finished, they instantly uploaded a recording of the session into AI software specifically designed and tailored for their industry, and in less than 15 minutes had access to the meeting summary, key topics of discussion, questions, and action points.
When the wealth manager then finished the second meeting, they already had a draft report ready for review to be sent to the client from the first meeting. The outcome? Massive time savings and a client who was grateful to get their report on the same day.
Now, imagine applying this example across an entire wealth management business. Each hour saved compounds, becoming hundreds of saved hours over the course of a year. This time can be re-allocated; more time spent with clients, more time meeting new clients, more time growing the business, and – crucially – all achieved with the same headcount and just a sprinkle of AI-powered resource.
Build and invest in your team
Employees are a wealth manager’s biggest asset. People connect with other people. Each advisor has the ability to understand their clients’ needs and build long-term relationships, but scaling people can be hard work, if not impossible. This is true, and not something I dispute, but I have seen new ways of supporting this process that have created greater efficiencies and helped bring people onboard faster.
The investment required in bringing new joiners up to speed is significant. Not only do you need to cover their wages as they come online, but all the time others in the organisation are spending to help bring them into the fold.
Again, this is where AI tools can help. One wealth manager I know has a very specific ‘fact finding’ script with points they want to be consistent across all initial meetings. It is essential all points are answered so they can move the relationship forward.
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Rather than let the new joiner present again and again to another member of the firm, they gave this new joiner an AI tool that allowed them to practice their pitch and get immediate feedback on their presentation. The new joiner practiced again and again, so when they were finally ready to present to their boss, they really were ready.
The outcome was impressive. Their presentation to their team was flawless from a content and delivery perspective, and the only feedback given was to use a different set of examples for different clients – but this was small finessing of the overall pitch, taking the new joiner from 80% to 100%.
This saved hours (if not days) worth of time internally and got the person ready to meet clients sooner than ever before.
Engineering for future success
I have yet to find a single ‘must have’ AI product for business, but I am seeing different tools appear to solve different problems. Technology will continue to advance at pace, providing more refined tools to more established problems.
The firms that are the most open-minded about learning and experimentation are the same firms that I have seen make the most progress with implementing AI tools in their businesses. These businesses created frameworks to empower their employees to go and find the tools that were most helpful to them.
My suggestion to everyone is the same: Get the necessary framework in place and start experimenting yourself. If you are stuck for ideas, download ChatGPT – not to supercharge your business, but to understand what an AI experience can be like.
The sooner you do it, the sooner you will benefit. And trust me, the results are amazing – I’m seeing them every day.
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