Maybe RPA is a gateway drug after all, as AI takes the number one spot for investment focus

November 19, 2019 | Phil Fersht

There haven't been too many better debates since RPA fever took over the world of process executives whether the toolset was the first step on the road to full artificial intelligence (AI) adoption. The consensus has largely been that RPA provides some great process orchestration experimentation that can eventually help us enjoy that ultimate AI high.  However, the only way to truly get on that Intelligent Automation Continuum is to redesign processes that drive specific business outcomes, where RPA is an enabler to achieving the desired process flows.  If you're just using RPA to make a crappy old process run better, you'll struggle to achieve much more than a mild buzz:

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However, what really brings home the emerging ambition of enterprise operations leaders is the new data from the State of Operations study that shows AI leaping ahead of RPA as the most significant area of focus for investment in 2020.  This clearly means that achieving AI effectiveness is clearly the larger enterprise-wide goal, and experimentation with process automation is encouraging many executives to think about broader business outcomes as the potential of machine learning and other AI facets become more and more intertwined with process digitization: 

The Bottom-line: Automation and AI strategy must be led by overarching business strategy, and RPA often provides the first testing ground 

If automation is not part of the overall business strategy then senior leadership should not be focused on delivering automation projects as they run the risk of failure or at least mediocrity.  Most businesses can really only deliver against 3 or 4 strategic initiatives at a time, so if automation projects are not directly contributing to one of them they should be stopped.  The focus of automation always needs to be on desired measurable business outcomes of these bigger initiatives, otherwise, they become too tactical and will lack management commitment. The short-term targets and KPIs need to have a clear and logical relationship to the bigger picture.

In addition, RPA must be treated as an enterprise application. If RPA is viewed as a widget or productivity utility, then it has no chance of supporting broader digital change. Part of business and IT alignment is recognizing RPA as part of the canon of digital change agents that are helping advance how companies are run. No tool alone can ever do the job. But the exponential power of “and” is compelling.

Posted in: Robotic Process AutomationArtificial IntelligenceRobotic Transformation Software

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  1. James Lawson
    Posted Nov 20, 2019 12:02 PM | Permalink Reply

    Useful insights Phil.

    We're certainly seeing a significant increase in demand to compliment RPA with Artificial Intelligence.

    AI means lots of things. We see interest specifically for making better predictions and decisions using Machine Learning models. For example in use cases like customer churn, fraud identification, demand forecasting, claims processing etc.

    The ideal scenario is not to use RPA and AI separately, with disjointed PoCs and siloed initiatives, but to combine them to automate complex end-to-end processes.

  2. Sunny Mishra
    Posted Nov 21, 2019 08:40 AM | Permalink Reply

    What happened to your AI part? Did you simply forget to add it to your article?

  3. Phil Fersht
    Posted Nov 21, 2019 09:29 AM | Permalink Reply

    @Sunny - it's the third chevron...

  4. Francis Carden
    | Posted Nov 21, 2019 12:43 PM | Permalink Reply

    AI is a very serious subject, and very strategic (carrying risks and rewards).. It can be used of course to help process unstructured content (documents, emails etc, ) stand-alone or using RPA to get data into and out of screens. Lots of vendors and 3rd parties doing this. BUT the MASSIVE bang for the buck is where AI is used to help processes and data as part of the "Process Digitization" you mention. We have clients processing 100's of millions of customer interactions a day, through our core AI engine (the Pega brain) to predict the next best thing to do, in the moment, in context and personalized. Something a human could never do, is done in < 100 milliseconds even with all this data. Better still, it's the business that can build the schemas and can set the rules (levels of transparency and opaqueness) necessary to drive the right kind of value and reduce the risk. We agree Phil. AI and Process Digitization on which RPA can help is a good thing.

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