If you ask Alexa, “what’s the meaning of life?” ‘her’ response is: “42” – a familiar reference to one of Britain’s favourite sci-fi classics, The Hitchhiker’s Guide to the Galaxy.
It would have been a bit much for anyone to expect a digital home assistant to definitively answer this question, which has stymied the world’s greatest philosophers throughout the ages. However, Alexa’s clever, ironic answer shows how consumer AI is evolving to become that bit more ‘human’.
As people grow increasingly dependent on AI in their daily lives, the same technologies proven in consumer devices, like natural language processing (NLP) and machine learning, are starting to permeate many business areas. Every day new applications hit the market promising to improve productivity in human resources, sales, marketing, manufacturing and finance. According to a 2017 survey by Boston Consulting Group and MIT Sloan Management Review, almost 75 percent of technology, media, and telecommunications companies expect to produce AI-based products in the next five years.
Despite much press coverage on ‘rise of the robots’ and similar Orwellian themes, many burnt-out office workers are starting to welcome AI’s potential to relieve them of onerous, time-consuming and error-prone tasks. Many of these tasks are maths-intensive, like analysing large, complex sets of financial figures or optimising inventory levels across multiple warehouses. Others involve finding ‘needles in haystacks’ like searching for data on break clauses in huge volumes of lease agreements to prepare for IFRS 16 compliance. Fortunately it’s these tedious, spirit-crushing jobs that AI is best at.
Freeing up human capital
What will knowledge workers do with all their free time? Simply, their actual ‘human’ jobs. Ironically the PCs that sparked the digital revolution that began in the early nineties generated more information than humans have been physically able to process. Unable to keep up with the deluge of e-mail and crunching customer, employee data and financial data, knowledge workers outsourced much of the interesting, creative, valuable work that required ‘thinking time’ to external agencies. This led to an unpalatable cocktail of corporate stress, boredom and an inability to ‘switch-off’.
Now that systems are becoming smart enough to manage all this data automatically, businesspeople are finally gaining the space to do things like develop and apply better management skills (much needed to raise UK productivity), deliver personal customer service, devise creative ideas for marketing campaigns and undertake long-term financial planning. It’s the office equivalent of home cooks realising that Alexa’s recipe-reading, egg-timing and metric-converting skills frees their hands to shape meatballs and roll sushi.
Incidentally, a World Economic Forum (WEF) report backs up this assertion. It estimates that 5.1 million jobs will disappear in 15 leading countries by the end of 2020. However the “Fourth Industrial Revolution” is set to generate a high demand for creative skills and a decline in office admin.
Finance has most to gain from AI
Because it is full of numbers by nature, I believe the finance world has the most to gain from AI technologies. Here are just a few ways I already see it being applied:
- Using NLP to scan huge volumes of scanned documents quickly to find key information essential for regulatory compliance.
- Collecting, consolidating and crunching numerical data to reduce quarter-end closing time.
- Making more accurate predictions for cash-flow and revenue forecasting, cost and expense planning, and balance-sheet planning. A key advantage here is AI’s ability to eliminate guesswork and “confirmation bias” (engineering a desired outcome).
- Using blockchain technology to secure financial transactions and share confidential information
Reskilling for the AI revolution
I’m not expecting all to be rosy for from the outset. Some people will struggle to upskill fast enough. There will be growing pains. So how can finance people prepare now to mitigate problems and make the most of the AI revolution?
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Firstly, reassess your skills requirements. With an AI-augmented financial system you are likely to need fewer humans to undertake tasks like reconciliation and more to do analysis and derive insights. Also, you are likely to benefit from employing people with a broader range of ‘soft skills’ like communications, stakeholder management and commercial understanding. You will likely need to upskill existing staff.
If your company will use algorithms for decision-making, it’s also advisable for some team members to learn the basics – the different types of algorithms out there and the situations in which each applies. You may also need to hire people with advanced technical skills to provide oversight on how algorithms are applied and ensure ethical rules are met.
If you haven’t done so already, now is also the time to upgrade your data architecture and management tools and processes. Our customers, like Laing O’Rourke, have benefited greatly from building a central data hub and introducing best practices for data hygiene, governance, security and compliance. You may need to recruit data or IT experts to help finance understand their data, including which sources can be blended to gain further insights.
AI might not be able to solve life’s deepest and most profound philosophical questions – nor is it ever likely to. However when it comes to improving productivity at home and in the world of business and corporate finance, AI continues going from strength to strength.