How AI can deliver value in business as it does in our lives

AI plays a critical role in our everyday lives, although the same shift is not visible in the workplace. It’s time to reflect on the disparity.

In brief

• The experience for enterprise processes has often delivered improvements rather than being truly transformational.
• One of the common pitfalls is not to re-invent the entire experience and instead use cases too focused on a single improvement.
• It is time to move beyond pilots. AI is often seen sitting idle after proving a narrow pilot.

This year’s summer holidays provided me with a stark realisation: how much AI has become an integral part of everyday life.

I spent a happy two weeks driving the south of Italy with my family. It was very enjoyable trip and provided a welcome rest. I cannot help but also reflect on the difference in the experience of driving abroad now and from before.

Ten years ago, our holiday started in a car full of little people failing to follow the printed route map from the airport towards our Eurocamp site. It was always the most stressful start to our vacation. Now, we connect Google Maps to the car and travel unburdened; the only arguments now are with our now teenagers on what songs to play on the journey.

This is just one of dozens of examples of how AI plays a critical role in our everyday lives, and for the main part, without us even realising it.

Alexa customises the morning news, Spotify suggests what songs to listen to with its Discover Weekly soundtrack, Netflix recommends what content to watch, Fitbit encourages the morning walk, and Ring notifies you someone is approaching the door.

We use AI in our lives with little thought but high expectations. However, the same shift has not been as prominent in the workplace with many enterprise processes remaining clunky. There are also some sectors with incredibly innovative AI applications, such as for cancer diagnosis and to support preventative health. However, such solutions are generally isolated and unconnected.

It is useful to reflect on why this disparity has emerged.

Transformation should be central for enterprise AI

The best digital solutions combine automation, analytics and AI within an innovative journey built around a deep understanding of the user needs. For example, Google Maps connects directly from Airbnb to confirm the location of our next holiday location. It also helps identify fun things to stop at on the route to ensure we arrive at the next property at the right check-in time.

These digital services have evolved based on detailed research to fully understand the current and future customer requirements. They are also essential as they compete on experience. Simply, if you don’t delight the customer someone else will. This experience is also underpinned by a breadth of data services to ensure a more customised and responsive service.

While acknowledging many successes, the experience for enterprise processes has often delivered improvements rather than being truly transformational.

Common pitfalls include:

• Using cases too focused on a single improvement and not re-inventing the entire experience

• The solution uses only a single technique resulting in:
  • Automation removing some onerous activities
  • Analytics offering a more targeted list but within the same business process
  • AI sitting idle after proving a narrow pilot.

The last point is especially common and can mirror Christine Connolly’s quote of having 'more pilots than British Airways' while CIO of the UK Department of Health. It is incredibly frustrating completing a successful pilot to then watch your masterpiece sit on a shelf and gather dust.

Part of the solution is ensuring leadership buy-in while selecting the pilots. For example, on a previous innovation programme we required our steering group to sign off the implementation of each pilot subject to it meeting agreed Go / No Go criteria.