It’s difficult to have a conversation about the future of work without mentioning artificial intelligence (AI).
And with a recent PWC report claiming this technology will create a net number of UK jobs (7.2 million by 2037, to be precise), clearly it’s going to have an enormous impact on our economy.
But in practical terms, how can you as an organisation use it to your advantage?
That was the question Fujitsu’s David Snelling and Dr Milos Milojevic from Pierre Audoin Consultants (PAC) aimed to answer during their breakout session at Fujitsu World Tour 2018, using insight from our recent joint report: What AI can bring to business applications.
Here’s what they had to say…
The story so far
First thing’s first: what do companies actually value most when it comes to the application of AI?
The most desired outcome by far, according to our report, is the ability to create a more personalised end-user experience (93%), while 69% want to enable real-time responsiveness and 64% want to build conversational interfaces.
While these are no doubt valuable functions, David referred to them as ‘surface AI’ – AI that sits over the top of an application, as with tools like Amazon’s Alexa.
True value, he argued, comes from “AI that sits at the heart of business problems.”
“Most people are looking at it from an operational perspective,” he added. “But not many are thinking about how it could impact their business strategy.”
So how are businesses applying AI already?
When you break it down by department, you can start to see the specific impact it can have within each area of your organisation.
- Supply chain management: increasing profit by identifying the best procurement strategy and optimising operations
- Accounting: automating time-consuming tasks like invoicing to free up time for more strategic thinking
- Production: enabling predictive maintenance and using automation to improve efficiency
- Sales, marketing and service: targeting customers with more personalised offers and understanding their reactions by analysing their faces and gestures
- IT: enhancing cybersecurity and using asset monitoring and predictive maintenance to improve service
Dr Milos also talked about some specific cases where brands have been using AI to create a major business impact, from Shell using AI chatbots for customer service to Virgin Trains using it for emails.
But some companies have come up with even more interesting use cases.
Pharmaceutical firms like AstraZeneca and GlaxoSmithKline have been using AI to develop personalised drugs for individual patients, while EasyJet has been using it to predict how much food it will need on flights to help control fuel costs.
Clearly there is already some exciting innovations happening with AI in business, but where do we go from here?
According to the Fujitsu/PAC report, the biggest future investment areas for AI will be:
- Tech to augment existing business apps (52%)
- Business apps that provide AI features (45%)
- Training internal staff (38%)
- Systems integration (28%)
- Hiring AI experts (23%)
- Process and strategy consulting (22%)
There will be some obstacle along the way, however.
75% of those surveyed in the report cited legal compliance and restrictions as a barrier to AI adoption, while 62% mentioned software vendors being slow to implement new solutions and 45% said internal processes and culture are holding them back.
But organisations have to overcome these obstacles if they want to truly adopt AI and not just test the water.
As Dr Milos put it: “Only when AI becomes part of your strategy do you begin to get the value.”
Dos and dont’s for AI
To round off the session, David and Dr Milos presented a list of things you should and shouldn’t do when it comes to AI:
- List your problems and business challenges
- Use what you have (data, tech, talent)
- Get to know AI use cases and vendor systems
- Personalise products and services
- Improve efficiency
- Talk about culture
- Do it because everyone else does
- Make big tech investments before thinking about strategy
- Forget that AI can bring automation and major change
- Forget to ask about quantifiable use cases when dealing with vendors
- Be afraid to learn from other players – even competitors
David also had a final warning for those thinking of rushing headlong into AI investment without first understanding how it fits in with their wider strategy and vision.
“If you jump too soon,” he said, “you’ll end up disappointed and wasting a lot of money.”
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