Although recent years witnessed an explosion in applications with a form or another of AI, business applications are still limited to a restricted set. Typical examples of AI solutions for business are in recommender systems for content or products, chatbots to ease customer service, intelligent virtual assistants to facilitate internal communication and workflows, fraud detection, bots to improve customer experience, or programmatic advertising and automated marketing solutions. Industrial sectors also benefit from AI developments mostly through intelligent control systems for industrial assets and processes, predictive maintenance, process monitoring and optimisation, autonomous trucks and other smart assets. Although overwhelming, these examples are only the tip of the iceberg when it comes to what AI can do.
Most of the applications I mentioned are prime examples of narrow AI. They are designed to resolve specific use cases. Nevertheless, these systems are working, and businesses have reported improvements in efficiency and productivity after adopting them. However, these improvements don’t come for free. Significant drawbacks on the road to broad AI adoption is not technical, but ethical and skills related. In a recent survey from InfoSys, senior business decision makers revealed that they are concerned about the lack of clear ethical standards when it comes to AI. Furthermore, business leaders are worried about the job displacement that AI will cause. However, AI is not just about automating processes and having machines perform human tasks. In reality, as AI adoption increases, new jobs will emerge from robotic and intelligent systems designers and builders to supervisors or other positions where creativity and intuition are essential. In a recent study, PwC study revealed sectors like professional services, science, and education would see a significant rise in the number of jobs available. Sectors, where people are performing repetitive tasks such as manufacturing or transport, will see a drop in jobs. Nevertheless, if people, business, and governments alike invest in the continual development of their employees’ knowledge, especially in STEM subjects and arts knowledge, companies will only have to benefit from adding AI to their workforce.
The future of AI for business is not all gloomy. However, how can companies transition from single, isolated AI solutions to enterprise-wide systems? A solution is to create networks of specific AI solutions and intelligent agents. These agents adapt to their environment and are autonomous. In other words, they continually learn from situations and each other about how to best perform their tasks. Soon, intelligent agents augment the whole enterprise and support employees. As they grow and evolve, these systems become ubiquitous, from internal systems to monitor and control processes to client facing applications and services. Thus, the enterprise backbone shifts from human decision makers to a mix of software or hardware agents performing repetitive tasks and adaptive and autonomous agents augmenting people.