Are artificial intelligence, machine learning and robotic process automation answers to questions that haven't been asked yet? The results of a recent KPMG study suggest there is a bit of flailing about with these hot new technologies now being aggressively pushed by vendors and analysts.
The study suggests there is hesitation, but in the long run, high hopes -- money will start pouring into what the authors categorize as "intelligent automation." In the next three years, 40 percent of executives expect to increase their AI investments by 20 percent or more, and 32 percent will increase robotic process automation (RPA) investment by 20 percent or more. These investments are expected to reach $232 billion by 2025.
Currently, only 24 percent have pilot projects or proof of concepts in place. Most executives acknowledged "they are still experimenting only with RPA, applied to legacy applications and processes," note Cliff Justice and a team of KPMG researchers. "With such a narrow focus and a bottom-up approach, they have not positioned themselves to transform their business and operating models so they can become and remain competitive with digital-first companies."
So, are AI and related technologies being implemented because they are the shiny new objects, or is there a business case emerging? At this time, executives "demonstrated high hopes but little readiness to drive IA deployment at scale and use it as a vehicle for organizational transformation," Justice and his co-authors state. The most pressing challenge is skills shortages, cited by two-thirds of executives. Another 50 percent report they struggling to define clear goals and objectives for AI deployment and accountability.
Challenges aside, "growing evidence shows that taking a strategic approach to IA by focusing early on creating new business and operating models can yield 5X to 10X dividends," the co-authors add. "The survey underscores that most organizations are still in the early stages of knowing where to prioritize deployment, how to measure true benefits, and how to address talent and change management issues."
A problem in these earlier days of AI and intelligent automation efforts is one that afflicts many technology approaches: goals that are too narrow. The KPMG team points to many AI and intelligent automation efforts that are targeted at automating legacy processes and applications, "which only improves efficiency incrementally and may have little impact on enterprise effectiveness and overall competitiveness." A strategic approach to AI should be about delivering "improved customer service, empowered employees, better
innovation, lowered costs, faster projects, and upgraded, standardized and higher quality operations."
To realize tangible business benefits, any IA effort should be an enterprise-level effort. "Individual departments can, and do, automate specific rules-based processes. Focusing exclusively on these types of efforts can waste time and resources that companies could better spend on an investment that will help the organization thrive and compete going forward."
