Exploring artificial intelligence in business: What are the potential capabilities and uses?
The most successful AI pilot rollouts start with a solid business case or challenge and clear success metrics. "Please don't be led by the technology," says Harrison. "As with any other technology that has come before, AI is just another capability. It's ultimately about first understanding your biggest business challenges and opportunity areas before trying to work out which technology fits."
In real-world terms, AI can be deployed for manual tasks that don’t necessarily require a human touch. For example, communications mining to prioritise customer inquiries and dedicate staff resources to moments that matter.
'We implemented this at a global vehicle leasing firm," says Harrison. "We managed to move their first touchpoint with a customer from over 15 minutes to almost instant and significantly reduced the time for the agent to phone. We could prioritise that for the agent because we could read the communication from the customer and identify where they came from.”
AI can digitise and process invoices across different formats by combining natural language processing with computer vision to read the text inside a purchase order PDF or a scanned handwritten document. It can also automate accounts payable and improve forecasting in finance through data-led predictive models, freeing finance experts for value-added work, like interpreting and acting on the outputs.
‘‘I'm in the middle of working with somebody from our data science team to try and work out how we can bring in multiple assumptions to improve our forecasting,” said one attendee. “So, you've got a multi-faceted type of linear regression that's then going to come up with multiple possibilities.”
Strategies for successful talent upskilling and change management
Most roundtable attendees agreed that talent shortages and change management were the primary challenges in adopting and scaling AI within their organisation.
Harrison recommends that business leaders approach it by covering a triangle of 'awareness, understanding, and expertise.' Employees should be aware of what the company is trying to do and how they hope to achieve it. Key figures with an understanding of the technology can be tasked with championing the initiative, and finally, the expertise at the top will deliver the capability.
“If you haven't got that triangle right, and you're top-heavy, you can have all the expertise in the world, but no one's going to adopt it because they're not aware. No one understands what you're trying to do. You can make everyone aware of AI, but if no one's there to deliver it, they'll easily get put off and move on to the next thing. That triangle is important to start your journey to implementing AI more successfully," says Harrison.
As AI becomes more prevalent in the workplace, the existing skills gap may widen. One attendee suggested empowering employees to embrace learning to help retain their competitive edge in the talent market and within the company.
"It's a real opportunity to tell people, 'Come on this journey with us. You'll learn these skills. You may not even use them within our business for years, but you'll be well equipped to go and use those skills in another business, and you're going to be valuable to people in the team who are willing to go on those journeys with you,'" she said.
“Ultimately, it's about upskilling and training. And where that happens is very organisationally dependent,” says Harrison. “If you're a fragmented organisation, then in-function or in-division normally works better. If you're an organisation that's very centralised, then centralised is normally the answer.”
