AI is far from being the new kid on the block, with its theoretical foundations laid decades ago by luminaries such as Alan Turing and John McCarthy. For businesses, it’s only recently become a reality. Those embracing it will be rewarded with greater efficiency, customer engagement and retention, as well as improved products and services. However, with so much noise surrounding the industry and offerings popping up just about everywhere, it’s difficult to decide the best way to invest in AI. Here, Craig Lodzinski at Softcat takes a look at the future of AI for businesses who are looking to adopt and adapt.
Take a breath before you dive in…
The AI industry shows no sign of slowing down, with the finance sector among the industries set to see the greatest benefit. In fact, it’s estimated AI processes could save the banking sector alone $1 trillion by 2030.
While we can expect to see many businesses leap headfirst into decisions about AI, those set to extract the greatest value will see through the fog and invest in the right systems to help streamline existing processes or add extra functionality to their offerings.
Many will be tempted to invest in the most innovative or creative examples of AI as a business differentiation or brand awareness exercise.
However, this is a risky strategy. AI investment should always align with the core of your business model. It should allow your business to work faster and smarter and generate cost savings.
For example, the online banking industry can implement AI services to help strengthen fraud detection, suggest personalised deals to customers and troubleshoot customer queries via automated chatbots.
AI can also help determine where prospective customers are in the sales funnel by identifying patterns of behaviour and allowing companies to serve them tailored information relevant to that stage in the funnel, ultimately increasing conversions.
The buy vs. build debate
Those ready to implement AI have an important question to answer. Do you buy pre-built AI infrastructure from a third-party vendor, or do you build your own from scratch?
There are benefits and pitfalls to both; it simply depends on your in-house capabilities and your long-term vision.
In the end, the decision tends to boil down to a few key factors. Larger businesses with mission-critical data sets and the manpower with the right skillsets could gain a competitive advantage by building their own systems.
On the other hand, smaller organisations may benefit more from outsourcing their AI function to external vendors and spending resource on maximising its potential.
The reality for many businesses in the early stages of AI will be a hybrid of both models. Investing in existing technology, while laying the foundations to build their own products in the future.
The next move
AI can be costly to implement and won’t transform a business overnight. Investments should be made with the goal of improving business performance in the long term and enabling better decision-making and more advanced capabilities in the future.
Business’ burning questions should drive decisions when it comes to AI. How can we retain customers? How can we make it easier for new customers to find us and buy our product? How can we solve our biggest problems like fraud or market competition?
For financial sector businesses, this could be AI aiding in the assessment of credit decisions. Data-fed AI can be used to review applicants based on a set of rules, relieving employees from long hours of manually assessing candidates and freeing them up to focus on other tasks.
Another example is compliance, which has traditionally relied on people. As the regulatory burden grows in the financial sector, organisations are starting to harness AI to automate a large proportion of the compliance function. Combined with management judgement, AI can streamline the process by providing a 360-degree view of an organisation’s current state of compliance and better protect consumers.
Whether you choose to buy or build, it won’t always be plain sailing. The nature of such a disruptive industry means there will always be issues to iron out. However, the doors AI can unlock for businesses is well worth the effort.
A common stumbling block for those venturing into AI is finding the right partners to help drive growth in this unchartered territory. AI has traditionally been an academic subject, with those able to apply it in a business sense being hard to come by.
As with tech innovations like cybersecurity, AI is suffering from a skills gap, meaning those who can attract the brightest talent have the opportunity to race ahead of the competition.
One small step for AI…
Although it appears AI has developed rapidly over the last few years – becoming a common part of our daily lives through devices like Siri and Alexa – the theory upon which the AI revolution has been built has actually been around for the best part of a century.
AI in its modern form is based on a set of complex maths and millions, if not billions, of data sets. While the realisation of AI technology has come about rapidly, we can’t expect to see the recent rate of growth continue.
The future of AI is expected to progress in small shifts, with significant developments occurring less frequently than they have done previously which is great news for businesses who are yet to invest.