We’ve distilled some of the highlights from Natalie Ceeney’s session here to keep the conversation and momentum going long after the event itself.

Let’s face it: we’ve been talking about machines spelling the death of human labour for at least three centuries. But the pace of technology is unstoppable, and with McKinsey pegging the average value generated annually by AI and Robotics at upwards of $50 trillion between now and 2025, there’s too much at stake to take a wait-and-see approach.

Certainly, on the cost side of the equation, robotics and automation will radically transform productivity as well as reducing human labour. But entire new industries will be born, with 300,000 new jobs set to be created in the UK alone. It’s hard to conceive what business will look like in 20 years, but amid the headline-grabbing disruption by pioneers such as Google and Amazon, much of the transformational work will be achieved by applying technology behind-the-scenes to basic functions like invoice matching.

Technology: once part of the business, now it IS the business

Nowadays, every business gets to know its customers through data, much of which is a digital exhaust trail of interactions. Whether we recognise it or not, our lives are already touched by AI and automation, from chatbots to reminders of physical services like parcel deliveries. What entrepreneurs can achieve today with a back room and £10,000 would have taken a server room and vast start-up capital a decade ago.

We’re already seeing AI and assisted bots replace routine interactions in contact centres, providing more efficient service and freeing up agents for customer-facing tasks that require uniquely human traits such as empathy and creativity. The automation of clerical work obviates the need for low-cost labour, prompting many businesses to bring back operations that were previously offshored.

Pattern recognition through AI and machine learning is set to see the biggest gains. In banking and insurance, identifying and quantifying risk is key to success, and the programs to do this will only get more intelligent and better at predicting individual outcomes rather than pooling risk. Similarly, studies show that in the field of dermatology, machines can objectively identify malignancies earlier than clinicians – whose human brains are wired to look for the familiar – by identifying new markers among vast pools of data that can be used to develop new models.

The ability for machines to get better over time means we will inevitably become more trusting of their advice: once AI is positioned not as Artificial Intelligence but Augmented Intelligence it will become an indispensable complement to human skills, in much the same way as we’re now accustomed to the majority of flying a plane being performed by autopilot.

Professional occupations, such as law, are at risk of having certain activities eroded by AI, as techniques based on natural language processing can be used to scan and predict what documents will be relevant to a case, yet tasks such as advising clients and appearing in court will remain beyond the reach of computerisation. At the macro level, education and professional training will need to shift from an emphasis on rote learning to critical thinking to ensure humans continue to remain relevant.

Fundamentally, organisations cannot afford to ignore the inevitability of change to their business models, or they risk going the way of Blockbuster, Kodak and HMV. The lessons learned from these high-profile failures were:

  • Never underestimate how attractive digital models are to customers, who may not favour human contact as much as we’d like to believe
  • Don’t underestimate the pace or scope of change
  • Don’t be scared of cannibalising your existing revenues – rather you than somebody else!

Four key predictions for the Finance function

  1. We will see the emergence of ‘finance factories’ supporting businesses in the way that IT today uses the cloud, with greater integration, and mobile-enabled, self-service tools for running simulations and analyses.
  2. Once liberated from manual analyses, finance leaders will become dedicated business strategists. Data modelling will determine the available scenarios, but ultimately it’s down to humans to apply those insights and take decisive action in the company’s best interests.
  3. The remit of finance will expand, with a greater emphasis on technology; indeed, we are already starting to see CFOs moving into CIO roles.
  4. As businesses become more complex, the finance function will become a unifying force, with areas such as the contact centre or R&D coming under its aegis.

The finance role of today is unrecognisable from the narrow accountancy role of 25 years ago, and no doubt will evolve further as it moves laterally into technology. But amid the growing emphasis on machines, the traits that will define the finance leaders of the future will be creative thinking and emotional intelligence.

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