Stanton Jones Research Alerts
What Is Happening?
Analysis of our recent global IT and business-buyer behavior study suggests that “ambitious” is the best word to describe enterprise plans for the adoption of software-based technologies and techniques that perform work like humans, or that mimic human decision-making.
Key findings from our new study, focused on the adoption of automation and artificial intelligence (AI) technologies in mid-sized to large enterprises, include the following:
- The application of automation and AI to mission-critical business processes will more than triple by 2019. Sixteen percent of respondents indicate that they have applied automation and AI to one or more mission-critical business processes today. By 2019, this increases to more than 50 percent. Interestingly, it is the application of automation and AI to mission-critical processes that is set to grow the most over the next 24 months, suggesting that IT and business leaders are becoming more confident that current proof-of-concept and pilot projects will move into production over the next two years.
Figure 1: Impact of Automation & AI on Business Processes. Source: ISG Insights 2017 Automation and AI Survey.
The rate of adoption of automation and AI technologies is set to double by 2019. Across nearly every technology category, planned adoption doubles. Survey results suggest businesses are looking to adopt technologies that have flexibility to solve more than one business problem and will target technology vendors and service providers that can solve a broad array of use cases. Similar to cloud, automation and AI adoption will be siloed until an enterprise-wide framework emerges to identify, evaluate, source, manage and govern various digital labor technologies.
Figure 2: Automation & AI Technology Adoption Today and in 2019. Source: ISG Insights 2017 Automation and AI Survey
- Outsourcing and offshoring is ripe for disruption. As ITO and BPO buyers increasingly look to automate processes before they outsource them, the need for traditional tower-based outsourcing services will wane – as will the need to have a significant number of delivery resources offshore. Buyers are also becoming savvier about the use of automation, and are realizing their managed services providers are not always passing savings back to them as services become automated.
Figure 3: Automation & AI Impact on Outsourcing and Offshoring. Source: ISG Insights 2017 Automation and AI Survey
Why Is It Happening?
Digital business is rapidly moving from the front office to the back office. Customers are not the only ones who need access to products and services in real-time – employees and suppliers do, too. However, budgets for business support functions are generally flat to shrinking, leaving little to no new resources to support back-office transformation. This is why IT and business buyers are increasingly turning to technologies like robotic process automation (RPA), autonomics and virtual agents to execute business processes faster, improve quality and compliance and avoid future costs.
As the front and back offices increasingly become digitized, transaction volumes are exploding. Technologies to store, process and analyze data are improving at a dizzying rate, and costs are plummeting. The combination of these two factors is leading to an unprecedented level of interest and planned adoption of the technologies that underpin this transformation, namely RPA, autonomics, virtual agents and assistants, and an increasing number of machine learning algorithms that can process large amounts of transactional data to identify patterns, determine viable options and make decisions.
As we recently reported in the ISG Automation Index report, service providers and enterprise buyers that are adopting automation and AI – and specifically RPA and autonomics – are seeing significant improvements in productivity, cost and speed. These technologies are augmenting their human counterparts, by automating routine, deterministic tasks. This is, in turn, changing the way enterprise buyers think about their operating model and their associated sourcing strategy.
Case in point: in the Automation Index, we identified a 43 percent reduction in full-time equivalent (FTE) requirements when RPA robots were applied to certain tasks in order-to-cash processes such as billing, cash application and credit. Along with a traditional labor arbitrage model with a large number of low cost offshore resources, A sourcing buyer also must evaluate a new model that has lower-cost RPA bots performing the bulk of the deterministic work and a small team of more highly skilled resources to manage bot exceptions and drive process improvement enabled by bot-produced data. These operating model choices will drive a fundamental re-think of the very nature of enterprise support functions – and will render irrelevant many of the traditional operating benchmarks we have relied on for decades.
Looking toward the horizon, as enterprises become more willing to embrace automation and AI, their number one issue will be talent – whether sourced internally or via a provider or partner ecosystem. Our research identifies data science as the most important skill set of the future and the one companies are having the least success finding and retaining. As we have discussed in the past, data science is at the heart of digital business. As software moves from supporting the business to being the business, finding and retaining data science talent will be critical to business success.