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Automation and AI Concerns – What They Mean and What To Do

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What is Happening?

ISG research into the adoption and application of automation and AI in user enterprises indicates no single factor, or even top-tier set of business or IT factors, specifically inhibiting widespread adoption of automation & AI. Instead, potential adopters cite a broad spectrum of known and expected obstacles, as summarized in Figure 1.

Figure 1: A Spectrum of Enterprise Automation Obstacles. Source: ISG Insights, 2017.

While there is an obvious rank order from top to bottom, and we can see some slight tiering, we see no significant separation from one potential or likely objection to the next. That makes it simultaneously more challenging, and potentially simpler, to overcome resistance to enterprise adoption (and adaptation) of automation and AI. This has important implications for those trying to build and prove automation adoption cases within the enterprise, and for providers seeking to introduce or advance automation in client enterprises.

 Why is it Happening?

What makes automation resistance/concern potentially more challenging to address is that there is no single target obstacle that promoters of the technology must overcome. There is no obvious “table stake” that simply must be addressed in order to start or sustain the conversation. Broad-spectrum circumstances like this also suggest that there is no single group of influencers to be convinced; there is unlikely to be a single influential group that will act as the bell cow to lead automation into and through the organization. The most likely outcome is that those wishing to introduce and promote the use of automation and AI must do so on a broad basis throughout the enterprise.

That’s also what can make this particular type of adoption-support-case challenge simpler to address. In this case, the list and ranking of concerns/obstacles is very similar to what we have seen with other emerging information technology applications, such as cloud, open source, social IT, and so on. When we see this type of broad spectrum we know that, even though there are uncertainties about it, the tech under consideration is widely viewed as an acceptable part of an overall business IT strategy. This suggests that most enterprise adoption leaders and influents can leverage previously-developed approaches to overcoming adoption obstacles.

That being said, a broad spectrum of factors or reasons inhibiting tech adoption also tend to indicate widespread uncertainty regarding what the tech is and what it can do. There is no shortage of useful insight and guidance, with associated business case support, especially from within the ISG ranks. Our automation survey report indicates a series of important business applications and benefits either being experienced or expected from the application of automation and AI within the enterprise; our ISG Robotic Process Automation (RPA) advisory group among others have done a great deal of work with and for clients in defining and explaining typical functions and tasks most applicable to RPA.

But we are still in the very early days of enterprise adoption, implementation, innovation and adaptation of many forms of automation and AI. In the blunt words of one of my analyst colleagues focusing on enterprise automation trends and developments, “The industry simply has no idea of what this can be.” Most focus today is still on the tech (e.g., RPA, autonomics) and techniques (e.g., machine learning, NLP) with relatively little understanding of which business functions these can help, and how.

Finally, much of the adoption of automation and AI by enterprises is being led by business groups – which helps to drive the broad base of interest and support, but also the broad spectrum of concerns. Automation is not seen by many of those leading the adoption as “typical IT” – because it is not “coded” but “learns” from data and trial/error. Most of the people that use it in daily business don’t need (or don’t think they need) to involve the IT organization – from their perspective, it’s all done via GUI, and there is no interfacing done. That leads to more disruption for the IT organization, and disassociation of the business from the IT organization.

 

Impact

A broad spectrum of concerns and objections to new types or applications of tech will continue as long as uncertainties abound. As with any and all new forms or applications of enterprise IT, education emphasizing real-world business and IT improvements is key to reducing uncertainty (and therefore, objections). Given that automation and AI are widely viewed as acceptable parts of an overall business IT strategy, typical forms of realistic enterprise IT business cases in support of will be applicable. Data and insights developed in our automation and AI research report and associated research (see below) will help in building such cases.

One interesting aspect regarding the spectrum of concerns is that automation itself can help to address and overcome several of the concerns, including those at/near the top of the broad-spectrum list, e.g.:

  • Budget concerns. Automation in most applications, especially within Finance, HR, and IT, will help to reduce some future labor costs, savings from which can help fund automation adoption and refinement.
  • GRC concerns. Automation within systems and applications (including within IaaS/PaaS/SaaS/BPaaS and related services) can be programmed and refined to ensure more and better compliance, and to more accurately flag and even repair non-compliance instances and issues.
  • Security concerns. Security is a doubled-edged when it comes to automation and AI (including bots). The risk is that its bots could be controlled by rogue actors inside and outside the organization, thereby acting as digital moles to do the bidding of a nefarious entity. But the risk is no different than what exists with today’s malware and threat actors. The unseen benefits – now just emerging in labs and early use cases employing automation, bots and AI – is that digital security becomes more predictable, efficient and effective, and reduces risks far faster and less expensively than humans and today’s perimeter approaches to security can ever achieve.

Developing effective approaches to address and manage leadership and organizational concerns are part of making automation & AI work in and for the enterprise – and key to provider services go-to-market success as well. Automation adoption and adaptation experience, lessons learned, best practices and more will be presented and discussed at the next ISG Automation Summit, September 19-20, 2017 at the Millennium Mayfair Hotel. Clients of ISG Insights will also see additional insights and guidance posted over the coming weeks.


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