A majority of organizations actively pursuing IA initiatives are often stalled by a lack of coordination, integration and prioritization, according to a new report by KPMG International and HFS Research. The study goes on to conclude organizations are becoming more ambitious with IA investment plans, but often overlook the full costs of an internal transition (which includes human resource issues)when investment plans are decided solely from a tech-centric perspective.

More than 30%of enterprises have already invested more than $50 million in intelligent automation technologies– so how can organizations move beyond pilots and into more scaled initiatives? Scaling has proven to be the largest inhibitor to IA success. Two other prominent challenges preventing strategic and operational goals from being achieved include an uncertainty about the financial investment needed in IA and a lack of organizational clarity and accountability for driving an IA agenda forward. Business leaders, including CFO’s, will need to decide what their company’s objectives are and then focus in on them.

A variety of recent data has taken note of the problem with IA pilots, regardless of whether they are specific to AI, RPA, or cognitive computing. MIT Sloan Management Reviewmade remarks last year of the 2018 NewVantage Partners executive survey, where 93% of organizations specified that their organizations were investing in AI initiatives.MIT Sloan approached many of the companies who participated in the survey to discuss writing case studies about their work, however, an overwhelming number objected to the idea.

Interestingly, most of the companies disclosed the reason they objected wasn’t because they wanted to keep their AI activities secret, but because they weren’t actually very far along and their projects were not worth discussing yet.Very few had production deployments and most of these were machine learning-based systems that had been in place for many years.

Even more, an international study on the future of work, conducted by IDG and LTM Research, found less than 50%of enterprises have deployed intelligent automation technology. These intelligent automation technologies include artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA). 86%of the IT executives surveyed believe that human work, AI systems, and robotic automation must be well-integrated by 2020, although only 12%said their companies are doing this well today.  Ultimately, the data revealed an enormous disconnect between the expected business benefits of IA and a typical organization’s ability to realize those benefits.

So how can we bridge the gap and move beyond pilots and into deployment? Unfortunately, there is no simple solution. Developing a solution will ultimately depend on an organization’s IA maturity stage: whether that stage is early adoption, implementation and evolving, maturing and scaling, or at various points (depending on an organization’s existing use of IA by department).

Regardless of what stage your intelligent automation project is in, we suggest you keep the following in mind:

  • No matter where you are, or what technology you are implementing, the core objectives and desired outcomes of pilot programs remain consistent; to meet your goals, understand your fracture points and identify what your need to do in order to roll out a successful initiative.
  • As part of your organization’s overall process improvement strategy, it’s imperative to continually evaluate your IA goals, strategies and performance measurements so to ensure maximum benefits from the opportunities at hand.
  • As an organization is undergoing significant digital transformation, you want to offer your workforce the skill sets they require to navigate their new work landscape, as well as offer them achievable career paths within their current job role and perhaps offer them new opportunities within your organization that have developed due to your IA programs.
  • As many organizations introduce a variety of IA technologies into their business landscape and culture, and/or further develop their efforts to do so, their diverse IT workforces may feel they require additional technical training, career development, and a sense they have a solid future at your organization.
  • There is certainly no shortage of highly valuable IA software that is available in today’s marketplace or will be offered in the near future. What may be considered a valuable IA software solution with respect to your stakeholders’ objectives, they don’t always prove to be a good investment on a technical level due to the complexity of technical roll out and management.

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