2022 will be a watershed year for the adoption of AI

In 1950, English mathematician Alan Turing wondered if machines could display intelligent behaviour. Over seventy years later, they certainly appear to do so. Whether as smartphone assistants, helpful search engines that seem to complete your thoughts, or as automobiles that warn of potentially dangerous traffic situations, artificial intelligence (AI) is all around us.

Yet, humans have barely scratched the surface of AI’s tremendous potential. The technology has already proved its worth, with companies in sectors such as heavy industry and oil and gas using AI to drive value for more than a decade. By some accounts, 2022 could well be a watershed year where we see a wider adoption of the technology in business and industry. As it comes of age, organisations will continue spending on AI to streamline their operations, reduce costs, boost efficiencies and foster value chain resiliency. Partly as a response to the pandemic, global AI software revenue is expected to total $62.5bn in 2022, an increase of 21.3 per cent from 2021, Gartner forecasts show.

Let’s take a look at some of the different ways that AI could be deployed in 2022 and beyond.

Different forms of AI are beginning to play together
The umbrella term AI encompasses many different scientific technologies that are applied in various ways. Machine learning algorithms, for example, use data models to make predictions. Reinforcement learning enables intelligent systems to test new approaches and adapt according to failure or success. Natural language processing helps computers communicate with humans, among other use cases.

We are now beginning to see multiple types of AI being applied within a single software environment to deliver an elevated solution. These different subfields – each a unique technology – are beginning to work together to enhance organisational capability and improve business value. Through a combination of AI and physics-based simulation, for example, we see cutting-edge analytics at work in predictive asset optimisation, where probable asset failures can be forecast alongside the provision of an optimised set of actions to mitigate losses. Machine downtime and production losses can thus be eliminated, evolving over time into self-healing autonomous machines, potentially saving hundreds of millions of dollars along the way for large industrial businesses.

AI systems transform human ability
AI systems are a natural partner for human intelligence, and we will see this synergy play out over the next few years as the world embraces the concepts behind industry 5.0. Already, AI models help human decision making by providing data-led insights to improve value and sustainability.

Now, computers are beginning to take an increasingly greater role in doing the heavy lifting and carrying out detailed analyses for their human partners. In the process, AI systems will make humans better at what they do. Repetitive tasks have already been automated away. The next step is reducing errors with better decision-making parameters and improved efficiency.

By providing humans with sophisticated, actionable guidance, AI will expand the scope of our jobs and enable us to do more things faster, elevating our ability and insight along the way.

Inclusive, bias-cognisant AI systems are coming
The all-pervasive use of AI will see humans delegate ever greater amounts of work to machines. In this context, companies will need to think about the data they are collecting, and how intelligence models consciously and unconsciously reflect real-world prejudices. When AI is applied to biased data, poor or improper decisions can result. Regulators will also begin to take notice of these technology biases. Eliminating these biases will be essential for AI solutions to be trusted and accepted.

Consequently, companies will begin to embrace responsible AI solutions built on principles such as fairness and transparency resulting in the use of comprehensive and inclusive datasets and better corporate governance.

Physics-based simulation combined with AI data models can help alleviate AI biases in the industrial world. The simulation software models real world processes and creates pseudo-sensors. When these are introduced into an AI model along with physical sensor data, it can significantly improve the outcome in terms of prediction accuracy and bias reduction.

AI will change the world as we know it
As a technology, AI has the potential to transform the way we do live and work. From industrial plants to environmental outcomes, AI will have a greater impact on industry and business than any other technology thus far in the history of the world. AI is merely in its infancy, and as it progresses, it will have an increasing impact on every person in every industry.

Just as the Internet began with email in the last decades of the twentieth century before expanding into the connected environment around us today, we are now on the cusp of realising and creating the multifaceted nature and value of AI. Its growing and widespread use indicates that 2022 will be the beginning of that transformation.

Read: Here’s how technology plays a vital role in sustainability