One prediction I have made about the future of service delivery automation (SDA) is that increasingly enterprise software will have the technology embedded. This is particularly true of intelligent and cognitive type of tools. I expect these to become a common feature of enterprise software in the next 5-7 years.
We saw this kind of trend in the earlier days of business intelligence and reporting. The popularity of third-party tools saw the functionality built into enterprise software. As well as reports on activities, dashboards started to feature in applications giving instant views of what was going on in the enterprise. We do not have to look far to find such software today, for example, Blue Prism, includes analytics that report on operations and performance of its robots.
A current example of a more intelligent enterprise software is Oracle Policy Automation Cloud Service. This reads policies written in natural language. Then based on business rules and the policy, it decides what questions to ask the customer, performs eligibility checks, and produces a decision report.
Another example is HighSpot, an enterprise search tool that uses natural language processing for searches and machine learning for finding the most relevant information and ranking the results.
The availability of open source machine learning software libraries, such as Apache Mahout, and software tools from industry giants, such as Microsoft (Machine Learning Service on Azure), will accelerate the next generation of smarter enterprise software.
Some would say that intelligent enterprise software would be function-specific, but I believe some varieties will be able to do more than one thing within large software applications. The need for standardization of interfaces to these tools and the ability to interact with other intelligent applications will grow over time too. We could even see more automations crossing paths across workflows leading to more complex machine-based decision making.
The question is what impact will pervasive intelligence have on the outsourcing industry:
- On the one hand, intelligent software will shrink the size of the workforce that is needed to fulfill many services and thus reducing the need for outsourcing
- On the other, intelligent software will open up opportunities for outsourcing processes that have not been outsourced before:
- These could be heavily document-centric processes, such as anything involving the administration and management of searching large volumes of content, for example, for legal discovery
- The processes could also be the evolution of other processes. For example, in hospitals we might see the patient “meet-and-greet” services outsourced to service providers who can also run basic health checks supported by AI engines to produce first-pass health assessments, before the patient is ushered to see a doctor
- Another outcome will be higher expectations of artificially intelligent outsourcing services; upping the ante for smarter outsourced processes – this is inevitable as those on the buy-side of the market become more and more accustomed to intelligent software.
Intelligent enterprise software is here. And we are on the brink of it becoming pervasive and commonplace. As it does, I’ll continue to share my insights on its evolution.
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