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Data, data, data: it drives the Internet of Things (IoT) as well as the surrounding economy. But to be of value, that data needs to be gathered, organised, queried, and analysed accurately. Moreover, the learning based upon that data needs to be understandable and actionable.
That’s where companies like Quantexa come in. Imam Hoque, COO and global head of Products at the data analytics provider, tells Internet of Business about the role of AI in analytics, and why he thinks AI’s day is finally here for smaller, as well as larger, organisations.
Internet of Business: We’ve been talking about artificial intelligence for a long time. So why do you believe it has finally come of age?
Imam Hoque: “Although AI has been around for a long time, over the past decade there have been some huge technological advances, meaning that AI is now capable of surpassing the decision-making skills of humans in many situations. AI now enables businesses to make decisions faster, more strategically, and for less money.
Previously, machine intelligence required a lot of computing power, so much so that it was not feasible for it to be an efficient alternative to human ingenuity. Now there are huge amounts of power readily available, such as Amazon Web Services, Microsoft Azure, or Google Cloud, which can run at $200 a day.
But as well as computing power, another key factor is data. Previously, data was not as easily accessible, but now it is everywhere and anywhere. Finally, the extensive implementation of digital strategies means that the AI brain can now be connected directly to customers with no need for a human in the middle.”
When we think about big data analytics and AI we often think in terms of large corporates. Can smaller organisations – say with fewer than 250 employees – also benefit? If so, how?
“Yes, absolutely. AI is an investment from which both large and small companies can benefit. It has the ability not only to provide a better service, but also to build on existing relationships and reach new markets.
AI can process large volumes of data, spot patterns, and make predictions, allowing you to act on new opportunities rapidly – which many small businesses may not have had the chance to do previously.
As well as spotting patterns and flagging them, AI enables small businesses to reach new markets by breaking down language barriers and time zone restrictions, enabling firms to establish stronger connections across the globe. This means it’s far easier to reach new markets – something that small businesses sometimes struggle to do.”
Are the costs of entry to using AI solutions falling for smaller organisations? If so, what is contributing to this fall?
“AI is now well within the reach of a small business. Now, you don’t have to worry about your own hardware, you can adopt cloud approaches and there is an abundance of open source technology and platforms, enabling you to choose one as a starting point and then add specialist commercial software if needed.
Universities are now churning out data scientists who already know how to use these open source technologies. The only thing you need to be careful about is if you’re processing personally identifiable information (PII), as you need to be aware of GDPR.”
Which sectors is AI having the biggest impact on?
“Pretty much every industry can be, and is being, impacted by AI. One of the key areas is in financial services, such as banking, where competition has become rife. Chatbots have already become a huge part of customer communication, cutting out the human middleman and therefore slashing the headcount.
As an example, AI techniques can process more data than a human. When combined with the scenarios shared by the best investigators, decisions can be made more accurately, consistently, within seconds and 24/7.
For example, a decision to alert an organisation of suspected money laundering can account for not just the transaction itself, but also the entire history of the company, how it compares to its peer group, all of the counter-parties it has transacted with in the past, and the full shareholding and director ownership structure – plus any other alerts that may have occurred in the past, together with their outcomes.”
Imagine you are talking to an organisation that’s just starting to think about using AI. What advice would you give them?
“Start by coming up with a candidate list of problems, and rank these in terms of business value. AI requires data to work, so go through each of your problems and check whether you have the data readily available for a system to make the automated decisions and interactions.
Choose the highest impact problems where you have the data available. Work out how you would use the data manually to arrive at the decision – you may need the help of a data scientist.
However, remember that you need to get your data into the right shape first. In the example I gave to the previous question, this would have required you to have first joined together all the data you have on a particular customer to produce a single view, and then linked that data into networks of relationships.”