A Thinking Business publication
With so much discussion about the grand potential of artificial intelligence to transform the way we do business, but also the many risks associated with getting it wrong, it can be hard for corporate leaders to know where to go.
Under enormous pressure to embrace the AI revolution, few can any longer afford to ignore it. But your business data is enormously valuable, so before you step into the world of AI, it makes sense to fully understand both the advantages and the challenges that you will need to navigate.
Advantages of AI for business data
Since the advent of Europe’s General Data Protection Regulation in 2018, every business has shone a spotlight on the way in which it handles personal data. Where AI comes into its own for many organisations, though, is in its ability to enhance business data analysis. AI can process vast amounts of data really quickly, identifying patterns and trends that humans might otherwise miss, and delivering predictive analytics that can significantly enhance business decision-making.
Victoria Robertson, partner in the commercial team at Trowers & Hamlins and a data law specialist, says: “Supermarkets might track how a particular brand sells in one place versus another, or what customers pick up when they first enter the store. AI can quickly identify patterns that might really inform where brands should be placed on shelves or what might be marketed to particularly customers in order to increase sales, for example.”
She adds: “Often it can spot trends that humans can’t, because we all bring our own bias and gaps that might stop us noticing certain patterns. The analytics that can come out might really make a difference to decision-making going forward.”
It can also play a big role in improving corporate efficiency. By automating data intensive tasks, speeding up data processing and reporting and providing real-time data analysis and insights, there is a lot of potential for both time and cost savings.
Then another big advantage is the potential for personalisation of the customer experience. Robertson says: “We are seeing businesses using AI for things like tailored goods and services, looking at where they have engaged with customers previously and then making suggestions. If the majority of customers that bought product A go on to buy product B, for instance, there is the potential for really customised marketing campaigns.”
Many businesses are also employing chatbots and virtual assistants to improve customer service.
Data insights can also be used to drive innovation, such as new product development, the optimisation of existing processes and services or even the identification of new market opportunities.
And, finally, cost reduction is often an obvious benefit that comes with AI investment. Savings can be achieved in a variety of ways, whether those are linked to streamlined data management processes or a reduction in the number of human errors that occur during data handling.
Robertson says: “There is a point where humans get tired and start to make mistakes, but AI doesn’t get tired – it loves these huge data sets.”
She adds: “With AI, it becomes possible to achieve much more efficient resource allocation, with data able to help you decide where you should be focusing your people, where are the key points that require human interaction, and what is the most effective way to deliver results.”
Risks of AI for business data
Of course, despite the many upsides that AI can bring, business leaders need to be mindful of the risks that come with such new and developing technologies.
A key area of concern remains data privacy and security, including the need to comply with data protection regulations like GDPR in Europe and the UK version of GDPR in the UK and other relevant legislation around the world, like the California Consumer Privacy Act.
Another worry is the potential for data breaches or unauthorised access. Chris Doherty, an associate in the commercial and data team at Trowers, says: “When investing in AI tools, businesses need to do thorough due diligence to make sure their data is going to be used in a compliant way, minimising any risks presented by AI use.”
There are also ethical concerns about data usage and AI decision-making that need to be navigated, which means checking the outputs from AI for issues like data quality and bias.
Doherty says: “There is a real risk that AI systems can perpetuate or amplify existing biases in data. Poor quality data can lead to inaccurate AI predictions and there can be real difficulties in both identifying and correcting AI bias, so training needs to be given to make sure those risks are mitigated.”
That problem is often compounded by the ‘black box’ nature of some AI algorithms, which makes them difficult to understand and means there is a lack of transparency and explainability. “Businesses using AI need to be able to explain AI decisions to stakeholders,” says Doherty. “If you are a regulated business, that is a particular issue when it comes to interacting with regulators. Otherwise, that lack of transparency can lead to potential legal liability issues in the event of claims.”
Data dependency can be a problem in some businesses, where organisations become too reliant on AI-driven insights. That gives rise to increased risks in relation to system failures or data availability, while also causing issues if there is a loss of human expertise and intuition.
“A lot of AI is intended to be used as an additional tool,” says Doherty. “It is not intended to be 100 percent relied upon, so you need human oversight. If you are only using AI and fail to check the outputs, you cannot necessarily blame the AI if it leads to mistakes.”
AI adoption can also bring with it significant integration and implementation challenges, because the tools and data infrastructure required can be costly and there are many options available. Leaders may face difficulties integrating AI systems into their existing data ecosystems, and the need for specialist skills and talent can make the costs prohibitive.
“Companies need to make sure they are acquiring tech that they can link into what they have and that they have personnel who can understand and manage the systems,” says Doherty.
Finally, there are regulatory and compliance risks associated with the fast-changing nature of AI laws. With different legislative positions being taken globally, as the EU’s AI Act leads the way and the American stance evolves under President Trump, organisations need to pay close attention.
“It is quite a difficult regulatory position right now,” says Robertson, “because the UK has not landed on what it is going to do. Companies need to comply with the EU AI Act if they are selling into the EU, and the position in the US is changing. President Trump has revoked the Biden Executive Order on safe use of AI and brought in a new Executive Order, with quite a different emphasis on American leadership in the AI sphere under the new administration.”
Taking a measured approach
With the AI technology itself also changing all the time, as we saw with the launch in January of a new AI chatbot by DeepSeek, a Chinese AI startup, keeping on top of AI innovations and risks can feel like addressing a moving target.
Robertson says: “The biggest concern we hear from clients is that if businesses are not engaging with AI and coming up with guidelines on how staff should use it, their employees are going to start using it anyway. That gives rise to a whole other set of issues.”
A report from LinkedIn and Microsoft published last year found that not only are 75 percent of knowledge workers already using AI at work, 78% are doing so without guidance or clearance from the top.
“For a lot of companies, having those conversations and being clear that existing usage is in line with policies has to be the first step,” says Robertson. “Having an AI strategy is now really important. For any business, there will be something that can be completely automated, so there are benefits to be reaped as long as the appropriate safeguards are in place.”
If you have not already done so, now is probably the time to wise up on all things AI.
