AI is moving from the ‘why’ to the ‘how’

Key Takeaways

UK business leaders are increasingly investing in AI, with 93% planning to increase their investment next year, highlighting a strong belief in its potential for business growth.

AI should be viewed as an innovation-instigator rather than just a solution for existing problems, necessitating a clear strategy for its broader applications to drive competitive advantage.

Workforce preparation is crucial for successful AI integration, as employees need to understand AI technologies and their implications to effectively leverage them for innovation and operational improvement.

When it comes to the growth and applications for artificial intelligence (AI), UK business leaders are enthusiastic. Ninety-three percent say that they have increased their investment over the last fiscal year and around the same number are planning to increase it again next year.

With many business leaders confident about the impact AI will have on the future, much of the hard work of convincing people of the technology’s value has already been achieved. Now we’ve established why AI is important for business growth the question many are now turning to is how it will be important for organisations.

Many business leaders are confident about the impact AI will have on the future

Currently, AI is frequently adopted in order to solve a multitude of business challenges. Part of the problem is the ‘AI hype’ that is circulating within the market. Many are trying to grapple with the technology to solve problems of all shapes and sizes. Getting a clear strategy on how AI and other related technologies can help a business is an area that still needs more work. As does the question of how to maximise the impact of AI and related proof of concepts that proliferate an organisation.

For instance, I have seen some organisations looking to develop AI systems to create personalised responses to customer complaints as they are no longer able to respond to these individually. The main challenge in this is that the number and complexity of complaints they are receiving is growing and this needs a broader solution. AI is an enabler to this – not the only answer.

Additionally, cost reduction is seen by many in the UK as the key rationale behind AI development. Many organisations view the technology as a straightforward way of freeing up workers for more value-add tasks and optimising processes like marketing and sales. Although it’s true that AI will be effective in pursuing these strategies, companies seeking a step change competitive advantage must build upon learnings from current priorities such as cost reduction to enable broader applications. 

AI is not a sticking-plaster for business challenges, but an innovation-instigator

To ensure that AI is not only developed to react to problems, but also proactively to pre-empt business challenges, the first step is to invest time in understanding the complexities of your business and the frequent challenges that customers and employees face.

Having worked for over 25 years in financial services, including insurance, one of the most frequent problems cited by clients is the struggle to collect high-quality, accurate and up-to-date risk data. 

In the world of commercial property insurance for instance, this data is relied on to produce risk assessments to inform the pricing, the monitoring of aggregate exposures, etc. However, teams are under increasing time and resource pressures and so collecting relevant data is a challenge. On-site visits are expensive and becoming less frequent and legacy information systems are quickly becoming outdated. In fact, it’s often impossible to visit all sites and in some cases only ten to 15 percent of commercial properties that are underwritten are fully assessed with an on-site visit.

I have been involved with the development of an AI tool which provides a digital print of any location across the world and access to the associated real time, on-demand data. 

The system is built on machine learning algorithms that extract, transform and combine unstructured and structured data. The algorithms draw on a range of sources, from open data, satellite and aerial imagery, social media, news, light detection and ranging (LIDAR) technology, and maps data. 

Built on Google cloud, the risk modifier data is then presented on a digital platform alongside additional analytics such as local surroundings, weather, and related history. 

Users of the tool have had their time freed up as they do not have to request and rely only on information from their customers and brokers. They are also able to rely on real-time intelligence rather than site visits and optimise which risks require physical inspection.

Fundamental to the development of this tool was ensuring that it incorporated data from globally and locally available sources of data and that users have easy access to understand how and where the data was collected. This ensures that teams have full trust in the tool and the recommendations it is making. In addition, this is more than just data, algorithms and cloud technology as it shows how AI solutions need to be engineered in order to make them scalable. 

Research shows that currently UK business leaders are half as likely to be using AI to create new products as business leaders in the US, Canada, China, Australia, France and Germany. Shifting our perception of AI as an innovation-instigator will be fundamental to ensuring that the UK remains a competitive market for the technology’s development.

Workforce preparation will be key to successful innovation and keeping pace with global competition

 UK companies today report more acute skills shortages than other countries particularly in technology roles. The biggest gaps in skills shortages in the UK compared to the rest of the world are in business leaders, change management and transformation.

AI has a tremendous opportunity to develop business, create new products and change our working lives

Workforce preparation will be key to successful execution and keeping pace with global competition. The reasons for this are twofold. Firstly, with a solid understanding of how AI technologies work and an awareness of the necessary data and infrastructure they depend upon, teams will have a greater ability to identify areas of where the technology could be applied to improve their day-to-day roles and increase innovation. Secondly, they will have a better understanding of how their roles will be adapted to work with the new systems once they are activated and the ethical considerations that must be contemplated when developing the technology.

AI has a tremendous opportunity to develop business, create new products and change our working lives for the better. However, AI is not the full solution and needs to be incorporated with other technologies to unlock the business potential. With the vast majority of business leaders now awake to the potential for the technology’s development and the impact it will have on their organisations, the next step will be to ensure that it is used to solve the right challenges in order to spark new innovation. Workers at all levels will be central to this task and it will be vital to invest in training at all levels to ensure that the UK continues to act as a leading market in AI’s development on the world stage.