It seems it’s become impossible to talk about IT, or business today, without talking about artificial intelligence (AI).

By Dana Eitzen, corporate and marketing communications executive at Canon South Africa

The technology has even been hailed as ‘the new electricity’. In April, Gartner announced that the AI industry will be worth $1,2-trillion in 2018, with customer experience solutions creating the most business value.

These solutions are unlikely to come in the form of robots on the shop floor, but solutions which provide customers with a more personalised and cohesive experience.

AI’s potential is attracting an arms race of global investment, with European governments scrambling to keep up with China and the US. In April alone, there was a flurry of announcements – the French government committed to invest €1,5-billion into AI research before 2022, the UK government pledged £1-billion and Germany announced special protection for AI startups against takeovers.

Meanwhile the European Union announced it was targeting €20-billion of investment by 2020. In a bid to nurture European tech talent, scientists have announced the launch of an AI research centre, based in hubs in the UK, France, Germany, Switzerland, Israel and the Netherlands.

It is easy to understand why, at least for the last decade, business have faced with the issue of how to invest in technology which will endure when the industry is evolving such an incredible speed. Organisations spending huge budget on new technology, do not want to have to consider a ‘rip and replace’ within three years. AI offers a new solution – technology which can evolve with us.


Sorting opportunity from hype

To truly become an AI business, organisations first have to get familiar with AI and what it can do. In Gartner’s list of top 10 Strategic Trends for 2018, the analyst claims AI has another two to five years before it reaches its peak in the ‘hype cycle.’ As we approach this peak, it’s important to review how AI can truly help your business.

Many technology trends reach a high level of hype which does not then translate into tangible business benefits. Think about how you can add AI capabilities to your existing products and services to provide demonstrable value.

One of the best examples is to enhance current business processes. For example, adding a layer of intelligence to data analysis. By applying AI to traditional business intelligence tools, the resulting dashboards are able to provide valuable predictive insights instead of simply telling a business what has already happened.

Meanwhile, businesses are increasingly using Robotic Process Automation (RPA) solutions which an evolution from traditional workflow automation tools, using AI to mimic human behaviour and perform more complex tasks such as collecting and extracting knowledge, recognising patterns and adapting over time.

In the words of McKinsey: “RPA takes the robot out of the human,” taking on the repetitive, manual tasks and freeing up workers to do more value-added, rewarding activities. As a result of taking on RPA, McKinsey reports businesses seeing significant ROI, that varies between 30 and as much as 200 percent in the first year.


Know your limits

Secondly, businesses should acknowledge their internal capability gaps. There may be a stark difference between what they want to accomplish and what they can actually achieve within a given time frame.

AI is such a diverse technology, from a tech and business process perspective company leaders should know what their organisation is capable of and what it’s not before launching into implementation.

For example, before deploying something like deep learning, businesses need to clean their data, to avoid a ‘garbage in, garbage out’ scenario. Internal corporate data can often be spread out in multiple data silos and may even be in the hands of different business groups with different priorities.

Forming a cross-business taskforce and integrating different data sets together, can sort out inconsistencies. This level of investment into the workforce and business processes is especially important in cases such as Purchase to Pay (P2P), or marketing, to ensure accuracy and compliance with the latest regulations.


Make incremental changes

It’s important not to try to introduce ‘big bang’ changes to the business, but to see the application of AI as part of the business’s evolution. For example, a retail company might start off by implementing intelligent triaging service within their call centres, ensuring that customer services are screened before being directed to the right contact centre worker.

At the mid-level, many retailers are building chatbots to deal with customer queries which harness AI to provide more intelligent responses. At the most sophisticated level, retailers such as Ocado have harnessed deep learning to intelligently detect fraudulent activity on their website.

Such a flexible technology is hugely useful to businesses as it allows them to stay agile, but implemented incrementally, it can give organisations a chance to prove value, collect feedback, and then responding accordingly.


Talent not just tech

Finally, it’s important to remember that it is not just the right technology which ensures a successful AI strategy. It is as much about fostering the right culture as it is about having the most expensive tools.

One of the best ways to do this is to prioritise investing in new talent, which can bring an influx of new thinking and innovation.

However, this in itself can be a challenge. McKinsey predicted that this year, the US alone could face a 50–60% gap between supply and demand for deep analytic talent.

The market is growing at a rate which is outpacing the availability of expertise. Businesses should look to invest in building the knowledge of current employees, building a foundation of understanding and awareness within the workforce through training.


An AI future

To truly become “AI-first,” companies need to understand that AI cannot demonstrate its full potential if it is used on an as-needed basis instead of being treated as an integral part of the business.

Organisations need to look for opportunities for AI innovation within the fabric of their business model, not only by integrating technology, but by building an AI-ready culture within the workforce.

By embracing AI, businesses have the opportunity to not only enhance existing products and services but create new ones. However, they need to use a critical eye to assess the market, adopting those technologies which can truly deliver tangible business benefits today.