Artificial intelligence (AI) has been around for years. It has crept into systems and solutions with determined, algorithmic intensity, and it has layered its capabilities onto chatbots, APIs, neural networks and business processes. It has evolved within the networks and the innovation hubs to become more than the hype that once preceded it. While it has yet to shift into robotic form and exceed the human, it has exceeded expectations in terms of its scope and scale.

According to Sabelo Dlamini, Senior Research and Consulting Manager, International Data Corporation (IDC) Sub-Saharan Africa, AI is now entering the commercial space at speed, bringing with it applications and solutions that can change the face of business – not explosively, but intelligently.

“AI has been around since the 1950s but today we can see its promise far more clearly,” he says. “It is promising a significant impact across multiple sectors and it can potentially solve problems of a global magnitude. Recent technological advancements in computing, storage and networking capabilities have enabled the viability of AI implementation.”

The technology that currently holds up the growing weight of big data and that ensures it is processed, stored and transmitted has become far more robust and scalable. Advancements in its abilities, and cost reductions, have made AI applications more commercially accessible today than at any time in the past. This is being further supported by ongoing research and development by organisations spurred by existing successes in the field. However, for AI to become even more relevant and accessible, there has to be a shift in business thinking.

“There’s an urgent need for business leaders to go beyond the AI headlines, which have mostly focused on machines replacing humans and causing job losses, and to look at more practical AI-powered solutions,” says Dlamini. “AI needs to be leveraged for business decision-making to complement humans, to provide more predictive and prescriptive analytics, and to unpack the vast quantities of data owned by the organisation. AI can be used in so many ways, and those ways do not entail job losses and human cost.”

With AI, the business can enhance employee productivity and skills development. It can automate the banal and change the boundaries of individual and business growth. But to do so, it needs buy-in from leadership and organisational culture. With this commitment, AI can go far beyond the hyped trauma of job loss and into the realm of improving business processes and customer experiences.

“A starting point for AI can be in embedding security throughout the business,” says Dlamini. “Using AI can enhance human analysis by automating repetitive security tasks and minimising error. It can also be used in threat hunting and detecting, stopping malicious activities, and analysing end points. Like the security guard who never sleeps, AI supports the human to provide a holistic security net for the entire organisation.”

AI is also being used to manage physical surveillance using video analytics and machine learning. Video surveillance systems rely on AI to interpret images and manage data at massive volumes, supporting the physical security of high risk areas and remote sites.

“Another concern raised by the business is the saying – use AI before it uses you,” explains Dlamini. “This isn’t as ominous as it sounds. It simply points to the fact that the business needs to take advantage of the technology before it gets left out, or left behind. Almost all sectors now have a case or application for AI, so every organisation within these sectors needs to take the opportunity to explore how technology can be of use to them.”

Today, to put the gears of AI in motion, the business should be putting proof of concepts (PoCs) in place that use AI to improve specific business processes. These PoCs should be focusing on the areas of the business where AI can complement human processes and where it can enhance different technology applications such as the Internet of Things (IoT) or robotic process automation (RPA). These technologies use AI at the back-end to improve business processes and augment the way the company delivers services in the future.

“While AI is continuously developing, there is still room for customising and localising the technology,” concludes Dlamini. “We’ve seen this already in voice recognition solutions that have been developed using AI to recognise local voices, accents and languages so that something as common as call centre technology can become fully relevant in a country like South Africa with 11 official languages. This is just one example of how AI can reduce friction in the business and make life easier and more profitable, in the future.”