How to Succeed with AI in Your Organization

Succeed with AI

Let’s talk about how to succeed with AI. As part of a crowdsourced article on achieving artificial intelligence (AI)-related success in IT service management (ITSM) use cases, I wrote a contribution that was long enough to be an article in its own right. So, here’s the guidance I’d offer to any organization that’s looking to successfully use AI-enabled capabilities to improve their IT service delivery and support.

Firstly, do plan to adopt AI-enabled capabilities

Organizations that don’t start to engage with new concepts will fall behind in skills and competitiveness. These tools and features are not yet very mature. Expect maybe 50% failure where the value doesn’t fit your organizational need, but with that will come 50% that will. So do get involved.

Are you an organization that’s looking to successfully use AI-enabled capabilities to improve your IT service delivery and support? Take a look at this guidance from @IanAitchison. #AI #ITSM #artificialintelligence Share on X

Next, pick the right tools to succeed with AI

It’s important to understand that AI is many things. It’s not a single technology providing a single solution. Much like a toolbox, you may choose to use a spanner, and a hammer, but not a screwdriver or the drill.

So, to succeed with AI, you need to consider what is available and pick the right solution for your needs.

So what sort of AI capabilities are there?

Broadly speaking, the AI landscape can be broken into solutions and features that:

  1. Analyze data and make recommendations. This tends to be the easiest to implement.
  2. Take action, either on request or independently. Often this is closely connected with automation tools
  3. Communicate. Here the natural language/conversational/AI pieces come to play.

Of course, sometimes you can also combine all three of the above in combinations.

Next, where are you getting those AI capabilities from in order to succeed with AI?

With #AI expect maybe 50% failure where the value doesn't fit your organizational need, but with that will come 50% that will, says @IanAitchison #ITSM #ArtificialIntelligence Share on X

Consider Built-In AI vs. Add-On AI vs. DIY AI

Many tool vendors in the ITSM, AIOps, experience management, and automation spaces are now offering built-in AI features in their technology that use various forms of AI and machine learning. These are the easiest to adopt. However, remember that an expert vendor in, say, service management, may not be an expert vendor in AI and ML. There is a higher chance that their AI features are light or lower-value.

That said, they’re the easiest to implement. So always ask what is the backend AI technology being used (third party or acquired proven strength here is an advantage). And ask for reference customers. Unless you’re willing to be that early adopter, which may be fine for your plans of course.

Then there are add-on AI vendors that – for example – may provide a chatbot that plugs into your automation or service management tools. These add-on AI tools are more expert and are more likely to carry greater feature power and value. But they’ll almost certainly cost you considerably more.

Considering #AI solutions? What type should you pick? Built-In AI vs. Add-On AI vs. DIY AI. In this article @IanAitchison looks at the pros and cons of each. #ITSM #ArtificialIntelligence Share on X

And, be very aware, some of the very mature complex AI does often come with a very significant cost and time overhead. The good stuff isn’t cheap and is often services heavy.

Third, there is the DIY AI build-it-yourself model. The value here is that your organization can learn how to use machine learning models and really take unique benefit, but this is a very significant investment of your time and resources, and carries very heavy overheads if you want to succeed with AI.

Finally, implement in small steps for AI success

Identify the best use cases and target these only if you want to succeed with AI. Phase introduction. Be aware of the culture of your organization. For example, pushing AI chatbots company-wide may well fail unless you’re sure that your entire company will really embrace the use of those machine-chat experiences. Many organizations struggle.

So, go point by point, use case by use case, and control target audiences until you’re sure it’ll work for you and your culture.

But don’t hold back. This innovation tide is already pulling ahead of many of us, and the water is rising fast. Better get in there and start swimming.

When it comes to adopting #AI you need to go point by point, use case by use case, and control target audiences until you’re sure it’ll work for you and your culture – @IanAitchison #ITSM #ArtificialIntelligence Share on X

If your organization has already been able to succeed with AI use cases in ITSM, then what advice would you give to others? Please let me know in the comments section below.

Ian Aitchison
Ian Aitchison
Senior Product Leader at Independent
Product Leader, Innovator, Blogger, Podcaster, Writer, Public Speaker, Board Advisor, Sailor, DJ, Musician, Bad Dancer.
As a vendor Product Leader, Ian has led the delivery and business growth of new and innovative SaaS & OnPrem products into the ITSM, ITAM, SAM, Automation and IGA markets over recent years. Frequent contributor to ITSM/ESM industry and community he is a seasoned public speaker and event-presenter.

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