Not just for big business: how AI went mainstream

A whole host of powerful technologies are becoming accessible to SMEs. Any smaller firm considering an AI investment would do well to study how the early adopters have fared
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Not so long ago, AI was the preserve of the largest organisations, mainly because of its cost and complexity. But this is starting to change. As the technology becomes more affordable, the largest hosting providers, such as Microsoft, Amazon and Google, are opening up access to shared resources and pre-packaged AI systems with offerings aimed at smaller businesses.

With AI becoming sophisticated enough to program itself, some leading technology providers are even delving into the world of ‘citizen developers’, as David Shrier, professor of practice, AI and innovation at Imperial College Business School, explains.

“This capability is growing closer. Under such a model, a small business owner would rent AI capacity from a large tech company and describe a problem verbally to the AI. The computer would then write a program for itself to solve that problem,” he says.

In the meantime, SMEs can start to benefit from the AI revolution by increasing their knowledge of the technology and understanding its underpinning principles. So-called low-code or even no-code AI systems are also available for use by those with no programming knowledge.

“Small business owners can become smarter about these technologies through online courses that provide insights into the field. They should also consider hiring an expert consultant,” Shrier says.

Smaller firms can adopt various technologies under the AI umbrella to enhance a range of operations. They could use chatbots powered by an expert system to cut their customer-service costs, for instance, or they could apply machine-learning algorithms to optimise their digital marketing expenditure.

Key factors to consider when evaluating AI systems include cost, ease of use and scalability. A smaller business will generally prefer a system that can grow with the company as its needs evolve and one that requires users to undertake minimal training. The most cost-effective way to start with AI is by applying it to relatively simple tasks on which it can have a big impact. This way, the firm is likely to achieve a faster return on its investment.

Founded in 2005, Neom Organics is a cosmetics company that employs about 150 people. The Harrogate-based firm is increasing its use of AI to automate numerous manual processes and improve their efficiency. But its overriding goal is to improve the customer experience it offers.

The company has developed a sophisticated technological infrastructure that it calls Neom IQ. This gathers data from across the business and uses it to power various AI-driven models, including stock demand forecasts, financial performance projections and the creation of personalised product recommendations for online customers.

The company has worked with a couple of AI consultants to “build out the ecosystem” and is now bringing in more experts in data modelling and machine learning, according to its CEO, Oliver Mennell.

“Once the system is set up, it isn’t complex to run, but it does rely on having best-in-class data integrity,” he says. “We work with some of the best technologies for our data warehousing, reporting and marketing capabilities, but have developed our own predictive modelling and personalisation tools in house.”

SME leaders don’t need high-level tech skills to adopt AI systems, but they do at least need to understand the basic terminology, the kinds of problems the technology is good at solving and the type of consultant they’ll want to hire to help them implement it.
Mennell adds that it’s “also critical to have a technology strategy and oversight of how these systems are being used in your business, because they will ultimately disrupt most, if not all, industries”.

Although several sophisticated and costly AI systems were available to Neom, it chose a relatively cheap, simple and adaptable option. This enabled members of Mennell’s team to become more hands-on with the data and build their own models.

“As we develop, we are adding more and more complex data sets and sources into the system,” he says. “We’re finding more innovative ways to use this data to improve the customer experience.”

By analysing huge amounts of data, detecting trends as they develop and recommending potential responses, AI offers smaller firms a much-improved ability to forecast new areas of demand – a key factor in fuelling their growth. But any SME leader who’s planning to bring AI into their company first needs to be aware of a couple of important caveats.

A key challenge for them is to ensure that any inherent bias, based on factors such as age, race and gender, is eliminated. They must also satisfy themselves that the people creating the technology have not embedded their own prejudices within it.

Will Richmond-Coggan is a director at Freeths, a top-50 UK law firm by revenue that specialises in technology and privacy issues. He advises SME leaders to “find out how the AI has been trained and what steps have been taken to eliminate or control for inherent bias in any training data set. You will need expertise to understand the answer. Such concerns can best be allayed by proper due diligence when you’re making purchasing decisions.”

Data protection can be another area of concern for SMEs. The specific rules within the General Data Protection Regulation that govern automated decision-making require additional safeguards. This means that smaller businesses will need to give more thought to how they inform employees and customers about what they are doing if they adopt AI systems.