Barriers to successful Intelligent Automation adoption

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What are the barriers to Intelligent Automation in your enterprise?

Many of the barriers to IA integration lie firmly within the existing IT landscape of the enterprise. Defining an end-to-end solution and then leveraging the appropriate enabling technologies against it, is a complex process and one that requires consideration of target operating models, tools, and underlying data. In combination, these implementations are powerful. But where the necessary integrations are lacking, problems emerge. 

The lure of lights out processing has been dangled before practitioners for two decades, and although intelligent automation is getting us closer, there is still plenty of work ahead.  Even if the technology wasn’t an issue, many organization still remain siloed making it difficult to gain agreement across functional areas on process ownership and design for an IA program.

The key hurdle for enterprises right now is integrating solutions into their existing environment. Particularly where these solutions come from the smaller startups that are driving much of the innovations, a valid concern is often whether that company will still exist next year. And if not, what happens to the investment?


Perhaps the greatest stumbling block is the fact that many corporations are still struggling with the rollout or upgrade of their existing ERP platform, so touting the "next level" of intelligent automation to build on top of that only highlights the current mismatch between expectations and deliverables (although, in terms of bridging the gap between ERP and applications, simple RDA/RPA are good solutions). Additional challenges concern the lack of bandwidth, and whether the business case really supports the desired outcomes – and let’s not forget that ERP providers themselves are busy developing additional capabilities, like SAP’s S4/HANA, which already incorporate many cognitive services through Leonardo and eventually, perhaps, may replace some of the innovative solutions that are making headlines today.

The decision around where to invest will also, to a large extent, be guided by where the enterprise has spent heavily on IT to date, reflecting its underlying commitment and priorities. Other factors include whether the knowledge to implement the new applications exists in house, along with the appetite for disruption.

Finally, with the future of what we might still call digital transformation firmly focused on cloud-based services, the question of server-based IA may itself become redundant or expose a corporation to future risk. The speed and the agility of the cloud is a huge attraction, especially in contrast to ERP’s regular and clunky maintenance and update requirements. Today's enterprises want quick solutions that integrate fast. IA is part of this, but the vehicle through which it is delivered will need to be as flexible as the solutions themselves.