This article will explore how artificial intelligence is set to impact organisations in the future, gauging the insights of experts in the space.
Artificial intelligence (AI) is changing how businesses work and interact with their processes, products and people on both the employee and client side of operations. Gartner predicts the worldwide AI software market to reach $62 billion in 2022, an increase of over 20%. This digitisation is game-changing for companies in all sectors, as it underpins smarter, more streamlined and more cost-effective running of businesses, as well as driving more agile operations in today’s disruptive climate.
With this in mind, we take a look at the possible future impact of artificial intelligence, as the technology continues to develop and infiltrate more business use cases.
Five AI predictions for 2022: from enterprise to everyday AI
Impact on corporate initiatives
Organisations of all sizes, across multiple sectors, look set to continue deploying AI as part of their business strategy. By taking a step back and applying a joined-up, strategic approach to implementing AI-enhanced technologies such as intelligent automation, leaders can derive clear business benefits, including – but not limited to – improved customer service, increased competitiveness, greater productivity, and a more satisfied workforce.
Eric Tyree, head of research and AI at Blue Prism, explained: “Whether it’s cutting customer wait times in financial services, enabling a more resilient and agile supply chain, or improving patient care by minimising manual admin work, intelligent automation can be the key driver in achieving strategic corporate initiatives.
“Being ahead of the curve in this respect will have a significant impact on an organisation’s competitiveness within the market.”
An evolving workforce
With AI-powered technologies in place to improve processes and transformation, organisations can then re-imagine how they operate, using a digital-first mindset. This, in turn, will allow staff to focus on more purposeful duties, including those focusing on customer service, and less on administrative functions.
Tyree continued: “Relatively speaking, intelligent automation technology is the easy part of process improvement and transformation. Intelligent automation makes the implementation of operational reimagination much simpler and is having a huge impact on the way businesses are looking at their workforce, ways of working and capability to enact change that has strategic value to the business.
“The capabilities digital robots possess lets the technology do the ‘heavy lifting’, allowing employees the capacity to take on more meaningful and complex work. The emphasis becomes a shift of human capital towards revenue generating or customer-centric activity, which gives way to enhanced capacity, more fulfilling work for staff, and more agility and scalability of resource across the entire organisation.
“As more businesses make the commitment to AI and other transformative technologies, we will see this impact more and more organisations for the better across the globe.”
In today’s fast-paced digital and commercial world, organisations rely on networks to operate day-to-day. However, to deploy the networking services needed to meet the demands of this new hybrid working world will now need a network that utilises artificial intelligence and other autonomous capabilities.
“Automation itself, and the idea that technologies can be self-provisioning, self-diagnosing, and self-healing, has existed for some time,” explained John Morrison, senior vice-president of international markets at Extreme Networks.
“But, thanks to advances in Artificial Intelligence (AI), autonomous networks are now becoming a reality. An autonomous network runs with minimal to no human intervention by configuring, monitoring, and maintaining itself independently. AI is now having a significant impact on businesses by replacing restrictive, error-prone networks and relieving overburdened IT teams tasked with ‘finding and fixing’ problems instead of ‘empowering and enabling’ people and connections.
“Everyone can benefit from autonomous networks, driven by AI. For healthcare institutions, such networks have the ability to, for example, connect a medivac chopper to the doctors on the helipad or monitor the IV pumps that keep a patient alive. And for schools, a connected classroom can be created to help children overcome learning challenges through supportive software or monitor attendance to proactively keep at-risk students engaged in education.”
Understanding your automation journey
Personalisation and customisation
On the customer side of things, users of digital services have been benefitting from AI deployments, which are proving to make engagement more efficient. While still relatively early in its development, artificial intelligence looks set to support bolstered personalisation and customisation over time.
“As we enter the new metaverse era, we will only have access to increasing data points, meaning we’ll be able to use AI more efficiently to create tailored experiences for customers,” said Maja Schaefer, CEO and founder of Zowie.
“In the future, our experiences with a brand will always be customised. For instance, when you enter a supermarket in the metaverse, the shelves will be stacked differently for others.
“AI is already driving better online recommendations and targeted ads. In the future, it will go beyond and impact interactions as well. Over the last few years we have seen more and more practical applications of AI technology, and in the coming years, it will become widespread. As AI becomes part of our everyday life, it’s important to remember and care for privacy. Data being processed should always be anonymised and used only for specific purposes.”
AI in industry
As AI continues to develop over the coming years, it will disrupt more operations across more sectors, leading to increased efficiency and decreased strain on workers going forward. The biggest impact from AI is set to come from those companies that can move their models into production most efficiently, and find ways to integrate those models best with their existing business processes.
Alex Housley, CEO and founder of Seldon, commented: “The highest transformational potential for AI likely lies in healthcare; despite currently sitting at a 36% adoption rate, healthcare applications such as improved diagnostics or protein folding can deliver exceptional social and economic returns.
“We’re also beginning to see other industries like construction and logistics leverage ML models to optimise their services. For example, the construction industry is using ML to increase the accuracy of estimates when planning projects and improve safety by detecting potential risks on-site to prevent accidents.
“We’re also seeing AI perform better, owing to improvements in how developers create models, alongside the ability for us to compress models and run them on edge hardware – allowing a greater variety of applications. AI is also becoming more accessible due to technologies like AI marketplaces, AI maker/teacher kits, and low-code/no-code AI platforms.
“All in all, these improvements dramatically improved AI’s use in industry, with nearly one in three enterprises having a model production by the end of 2021.”
Machine health in manufacturing
Manufacturing will see great potential for innovation, through an emerging framework called machine health. This capability uses the Internet of Things (IoT) and AI to predict and prevent industrial machine failures, and improve machine performance, via analytics.
Saar Yoskovitz, CEO and co-founder of Augury, expanded on how this is set to impact manufacturing operations in the future: “AI is spearheading the fourth industrial revolution alongside technologies like automation and IoT capabilities.
“Manufacturing is one of the industries already seeing a great benefit as AI is used to provide greater visibility into the processes, efficiency and capacity of these businesses. A key example is machine health – a solution driven by AI to provide predictive analytics on critical and supporting equipment within manufacturing plants.
“Sensors capture vibration, temperature and magnetic data from industrial machines, AI diagnoses machine issues based on that data and input from human reliability experts, explains what caused them and prescribes courses of action.
“The impact of this AI use case is huge. When a critical machine fails, an entire production line grinds to a halt and that has serious upstream and downstream effects on entire supply chains. Machine health, therefore, allows manufacturers to strengthen their resilience against supply chain issues, or global events that impact production.”