The AI Vampire at the Door

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Dsf 24

The AI Vampire at the Door

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last updated:

They found it difficult to comprehend its potential applications and were vocal about their struggle to reconcile the hype with the practical business value of AI.

I’m just back from attending and speaking at the annual DSF event in Boston; historically, the conference focused on CXM (Customer Experience Management)/CCM (Customer Communication Management) or, in other words, managing and often creating the masses of incoming and outgoing mail. It’s a niche sector critical to healthcare, insurance, and financial services. However, this year at DSF, in line with many other conferences, the key themes that emerged were the impact of AI and automation. Although I may be suffering a case of confirmation bias, many of the same concerns and interests I have heard elsewhere (most recently, Supply Chain Management) were echoed by the attendees and speakers alike.

One of the most striking observations from DSF was the collective unease around AI. Despite being tech and business-savvy, the DSF attendees, many of whom are key decision-makers, expressed their reservations about AI. They found it difficult to comprehend its potential applications and were vocal about their struggle to reconcile the hype with the practical business value of AI. What came across most strongly at DSF was the desire to automate, which drives almost every new IT project decision, and the desire to do more with less, not technology trends.

That’s not to say we didn’t discuss technology trends; there was plenty of talk about IDP (intelligent document processing), process mining, RPA, and advances in CCM and CXM. But, in the sessions I attended, those discussions were much more practical and grounded than similar presentations I have heard in past years.  A standout presentation for me was Rich Medina (Doculabs), talking about and sharing case studies and practical approaches to automation in Financial Services. In particular, his focus on the value of process mining to both fast-track business analysis but also to gain a much more granular understanding of how business processes are currently working in your organization. One specific example he provided was of costly business applications that executives believe are driving automation. Still, process mining revealed they are simply systems of record to be updated after completing the task or process. The work is, in fact, not automated; it is largely manual. In many regards, this was echoed in Tori Miller Liu’s (CEO of AIIM) presentation of recent findings from an industry survey that revealed that very few organizations are leveraging systems like RPA or BPA and that manual automation (if there can be such a thing) is the norm.

One mental image I left with was a quote that I am mangling from Rich Medina; in short, he said that AI is like the vampire at your door. It can’t come in unless you invite it to. No matter how charming, intriguing, and good-looking the vampire might be, you know you are likely asking for trouble if you open the door. Less eloquently, I think the approach to enterprise AI should be based on the concept of constructive cynicism. Or, to put it another way, rather than letting external events (AI and Tech Hype) sap our time and energy, we can instead choose to direct our actions inwardly and figure out what we need and are trying to achieve. If DSF is anything to go by, few organizations are close to AI readiness; there is a huge disparity between the perceptions of executives, line managers, and coal-face workers regarding their current operational activities. Furthermore, even where systems are automated, the data those systems contain is far from clean, and a lot of work needs to be done to sort that out. The looming question is whether all that work is going to be worth the effort.

So, back to my constructive cynicism angle, DSF was the latest in an increasingly long line of events and conversations I have had with end users and systems integrators that independently confirm unified concerns. Technology vendors must heed these concerns, build solutions to real-world business problems, and acknowledge the hard work of delivering valid and valued outcomes. In my talk, I stressed that there have been considerable advances in enterprise technology (particularly AI) over the past few years. The technology works well, particularly in demonstrations with clean data. But they don’t work in isolation, and very few, without heavy lifting, thorough change management, and a lot of honest reflection, work well in production.

Finally, a big shout-out to Allison and the DSF crew for putting on such an excellent event. Good conferences are tough to pull off, but they are a vital part of our industry. They are where we get to break bread together, share stories, and learn from our peers. In a world of tech hyperbole, they have never been more essential.

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