Artificial Intelligence (AI) offers organisations the chance to realise a vast range of operational efficiencies – but is it the right fit for your business?
When people talk about AI for business, what they’re really talking about is new ways of managing data – neural networks, iterative learning, pattern recognition, and the like.
While each of these technologies offers unique benefits, they’re usually grouped under the heading of AI, as they share four common features.
With these features, it’s not hard to see how modern businesses might stand to benefit from AI solutions.
AI’s features can have a massive impact on your daily workflows. These impacts include:
While these outcomes make AI sound like a productivity guru’s professional fantasy, AI still has its flaws.
While AI has come a long way in recent years, it’s still a long way from foolproof. Before integrating AI into your business processes, it is vital to be aware of the potential risks that come with its use.
AI are limited – like any other program, AI responses depend entirely on input. This makes them incredibly useful at generating specific outputs but unreliable at related tasks. For example, ChatGPT is an excellent natural language chatbot, but it can not source references. If asked, it will generate references that sound plausible – but these are fabricated based on the rules gleaned from the AI’s training data set.
AI can fall into the uncanny valley – while AI can respond accurately to human behaviour to an impressive degree, they still have limitations. Some AI-powered interfaces can generate photo-realistic images of complex scenarios – but when you count the fingers on any individuals present, you get a total that doesn’t add up. Or they may respond to emotive inputs with insensitive content. This experience can result in customer frustration and loss of loyalty.
AI systems are vulnerable to cyberattacks – it’s well known that cyberattacks can cause significant financial damage to any organisation. Cybercriminals can exploit vulnerabilities in AI systems to gain access to sensitive information. Or they may tamper with AI data-sets to produce useless or damaging outcomes.
As with most information technology, the question of fit comes down to your individual organisation.
Many industries stand to benefit from AI – particularly those that involve data processing, repetitive tasks, and personalisation.
However, a Gartner primer on artificial intelligence states that it’s important to first understand how AI developments impact on “…the fabric of IT departments…” – and that rushing in to this latest trend is not advisable.
An ad hoc approach to AI isn’t sustainable.
There are some markets – and some IT setups – where AI is not yet a good fit. These include industries that require a high level of human interaction, such as healthcare, hospitality and education. In these cases, AI can work in the background to help streamline service delivery – but they aren’t a good fit for every element involved.
The same can be said for heavily regulated industries such as finance or law. Organisations might find themselves hard-pressed to keep up with AI’s rapid pace of innovation, as their regulatory landscape may make it challenging to involve AI in many activities.
Finally, industries where data privacy and security are of utmost importance – such as government or defence – may have concerns about entrusting sensitive information to AI algorithms. That said, even these industries may find that specific AI applications can still provide value and should be evaluated on a case-by-case basis.
Integrating AI into business systems requires a measured approach that takes into account your organisation’s unique needs and goals. The steps listed below can help your business ensure it’s ready to integrate AI into daily operations.
While this list is generic, and does not cover every single step involved, it does cover important questions that require careful consideration.
Ultimately, integrating AI into a business requires a holistic approach that considers the organisation’s unique needs and goals. And the age-old practice of calculating your return on investment should be a main factor in your decision-making process.
When considering the ROI of an AI solution, the formula should include the costs of solution licensing, implementation, customisation, management, and hardware. Any savings or value-adding benefits have to reach beyond these costs in real-dollar terms for AI to make sense. Otherwise your organisation is investing in AI because it’s a cool thing to have. Maybe that’s good from a marketing perspective – but only if that also offers a return on investment.
As a decision-maker, its best to work with your internal stakeholders to assess if the outcomes and benefits of AI are a good fit for your organisation – and if it is, to then identify areas where you may need to invest in new technologies or talent to make it work.