Does Your Business Really Need AI?

As interesting as understanding what AI is and how it works, the most relevant and compelling question for any business is answering the question if and why they should use it. Whilst the specifics will vary for each business according to industry, vision and goal, there are some key aspects that form the basis for every answer. 

For any organisation, the foundation of the business case for AI will be based on three elements: the business objectives and the decisions made to achieve them, the predictions that inform decision-making and the value realised by acting on those decisions faster, more accurately and consistently over time than existing methods or by unlocking some new capability. This foundation must then be built upon, addressing factors such as data, technology that presents a viable solution plus the human and financial resources to develop and implement. By following this approach, business leaders will ensure they establish a clear business imperative that is agnostic and will form the basis for each of the other domains, allowing needs to direct AI initiatives rather than preconceptions based on technology or data.

Themes of AI

The simplest themes for most organisations will involve cost reduction or revenue growth and applying AI to support this by optimising and automating a key business task, such as automating back office tasks, demand forecasting and inventory management or pricing strategy. Some businesses may investigate the new and novel applications of AI to enable new capabilities, such as personalised healthcare or to create music, art and film. Each of these cases are distinct and unique but what each has in common is that to someone they are high-value decisions that can be made more effectively with high-quality predictions. Part of the challenge organisations face in getting started with AI is identifying the types of high-value decisions they must make, how they should be prioritised and which are feasible to augment by introducing new technology. 

To be clear, decisions do not refer solely to instances in which a human is actively required to make conscious, creative or critical decisions. Whether we choose to think of them in this way or not, organisations are made of decisions. Processes, operations and workflows are all comprised of decisions; be it hundreds or hundreds of millions, be they stand-alone or interconnected. For a given business, decisions may take place every microsecond across different platforms, applications and solutions all integrated together to form the complex technology lattice that enables the organisation to perform its services and create benefits for customers, whether an online transaction, money transfer or serving a digital ad on a website. These are all different types of decisions and as such, each requires its own unique logic to inform what decision should be made under different conditions and circumstances. 

Currently, the ‘logic’ used by traditional systems and processes are explicitly programmed by humans into what is often an expansive and complex series of programmed instructions that essentially can be distilled into “if this, do that”. Humans program the rules of a task and the conditions under which certain rules should be executed and the machine performs them diligently. However, this approach has well established limits. There are many tasks which are too complex to program all the conditions and outcomes as well as tasks that we simply do not know how to program the machine to perform. These limitations have led to the rise of artificial intelligence to solve complex technical problems and the possibility presented by these technologies has captured commercial imagination and interest across industry from healthcare to marketing to automotive; with dreams of a future where AI enables early detection of disease and personalised treatment, where all marketing communications and offers are truly unique one-to-one and a world where self-driving cars become smarter the more they drive and are interconnected with other cars on the road resulting in fewer accidents and fatalities. The opportunity represented by AI is to introduce human intelligence into situations in which human logic and judgement is desired but human involvement is not feasible, scalable or otherwise limited due to some constraints on humans such as analytical skill, accuracy or speed. By embedding this capability in machines we slip the constraints of traditional human and machine limitations and are able to align human goals with the sheer analytical power of machines to overcome challenges and barriers that were potentially insurmountable unless the strengths of both were combined. 

The power of AI is the ability of machines to make accurate predictions regarding outcomes that enable humans to better act in the future. Machines analyse what is known to ascertain relationships and predict outcomes that help humans anticipate the unknown. In doing so, machines help humans understand our world and vice versa. Although of high interest and value, humans lack the raw processing power to divine the depth of insights from data that machines, equipped with the right tools, can deduct far more readily (albeit they are far less adept at generalising learnings across tasks or context). Paradoxically, despite the efficiency and effectiveness with which machines may perform their task, fundamentally any and all information is arbitrary and presents no intrinsic value to machines as they lack purpose; they are devoid of the why.

Is AI the best solution to your problem?

Viewed from this perspective, AI is a partnership. Humans chart the course into tomorrow and machines help us navigate through the imperceptible fog that is the future. For now, the capability of AI is narrow; a specific tool for a specific task and humans must take the lead in deciding which is appropriate, based on our goals. One day this partnership could evolve into a form of symbiosis, with AI sharing our goals and becoming so intrinsic to our way of life that we can’t truly function or achieve our full potential without it, in much the same way as most people are likely to feel about modern technology. Perhaps even more compelling is the potential for AI to improve our understanding of how human intelligence works and what drives our behaviour. Replicating human intelligence in machines may end up being the greatest introspective experiment in human history that results in a new age of enlightenment and understanding.

But for now, this is postulation. The value AI presents to people and business right now is its ability to make better predictions that inform decisions to solve problems and achieve goals. To get started with AI, begin by setting aside the technology. Ask yourself what problems your business needs to solve, the challenges that need to be overcome and why this is important. Explore until you’ve hit the core of the issue, free from all the hype, only then you will understand whether AI is your answer or whether you can achieve your objectives using a simple linear regression.