Decoding AI for IT: 6 actionable insights for technology leaders in 2024

Every time I speak with an IT leader to understand their processes, priorities, and problems, I learn something new.

But lately, one thing has been coming up fairly consistently – AI in IT.

How you leverage AI in IT will depend on your business, target customers, organizational culture, and other nuances. But we’re past the question of whether you leverage AI.

There’s no putting this genie back in the bottle. According to Gartner, “By 2030, every dollar of IT spend will have an AI component”.

We, at Atomicwork, wanted to help IT leaders understand what their peers were doing around AI, so they could benchmark their own AI adoption. So, we collaborated with our friends, Stephen Mann and ITSM.tools, to conduct a study aimed at exactly this.

The results were published in the State of AI in IT, 2024 report. If you haven’t seen it yet, I would recommend you do. You’ll find a ton of rich data and insights from industry experts.

I want to share a few actionable insights from the report, so you can go into 2024 with an informed AI strategy:

1. The early-mover advantage

Insight: 58% of organizations are still in the early stages of AI adoption. 

Action: Get a head start on competition by leveraging this period for strategic planning and low-stakes exploration.

How soon businesses start taking AI seriously will determine the winners and losers once the dust settles. IT leaders will soon be inundated by the C-suite and the board to account for their AI strategy, adoption, and impact.

2023 was the year of tinkering with AI in general and GenAI in particular. 2024 will be the breakout year for AI in IT. Technology leaders need to start running small experiments, learn fast, and adapt to solve the business’s internal and external challenges.

2. Perceived benefits of AI

Insight: Top benefits of AI include ‘data analysis and synthesizing insights’ (45%) and ‘chatbots for self-service adoption’ (38%).

Action: Focus on these areas for maximum impact. Leverage AI to enhance data insights and streamline customer interactions.

We asked IT professionals, “What benefits do you anticipate or have realized through AI?”. I have to admit, this one took me by surprise. Data analysis and synthesizing insights emerged as the top answer. I’m assuming it reflects more “anticipation” than “realization”.

Either way, there’s no denying that AI can do a vastly better job analyzing large amounts of data. The evolution of analytics capabilities goes from Descriptive (what has already happened) to Predictive (what could happen) to Prescriptive (what should you do). AI can help businesses leapfrog to prescriptive analytics by finding patterns and identifying the path for maximum impact.

Chatbots were the second most popular application of AI. This is a no-brainer. That said, IT teams need to be mindful of end-user behavior and expectations. I’ll unpack that in a bit, but to put it bluntly, an AI chatbot would be great for deflecting repetitive IT (and HR) queries but for complex troubleshooting, users will need a human touch.

3. Barriers to adoption

Insight: The main challenges to AI adoption include ‘customer data security’ (42%) and ‘additional costs’ (39%).

Action: Prioritize addressing these concerns in your compliance planning and IT roadmap. Emphasize security measures and explore cost-effective AI solutions.

On the flipside to the perceived benefits, we asked IT folks what was stopping them from taking the leap.

The top barrier to AI adoption was ‘data security’, which aligns with the conversations that I have with IT leaders. Almost, 40% of folks mentioned cost as a barrier, which reflects a short-term focus. At scale, AI will drastically reduce operating costs even though the upfront capital expense may be high.

Another big surprise was that more people were concerned about ‘inaccuracy and hallucinations’ as opposed to ‘governance and compliance’ which is something that more IT leaders should start thinking about.

‘Lack of expertise’ also ranked fairly high on the list. Let’s talk about that and the cost concern.

4. Resource allocation for AI

Insight: 60% of organizations allocate at least 5% of their IT budget to AI. And 65% of organizations have two or more people focused on AI.

Action: Consider AI investments as catalysts for long-term success.

Gartner analysts claim that ‘By 2030, every dollar of IT spend will have an AI component’. I believe that broadly all B2B products and services will leverage AI much sooner, or risk becoming obsolete.

The AI race between Microsoft, Google, Meta, and others will benefit organizations in general by providing them with the infrastructure to build AI capabilities in-house.

Even the solutions you use for IT service management and operations management etc. will come bundled with AI. Most of these will start with GenAI and increasingly add more sophistication as the technology becomes more versatile and compute-efficient. 

In terms of expertise, more businesses will either hire or develop talent that specializes in developing and applying AI. This would either be located centrally or deployed within different functions.

I would lean more towards the latter model. An integrated AI expert who has an ear to the ground and also understands the technology is more likely to develop pragmatic solutions.

5. Strategic AI no-go areas

Insight: 41% of the respondents believe AI shouldn't be used in ethical decision-making.

Action: Establish clear ethical guidelines for AI applications at the workplace. Ensure responsible and transparent AI use.

A question that we asked, that we didn’t see others asking, was “Which areas of the business would you like AI to not penetrate?”. We were expecting interesting insights from this one and the respondents didn’t disappoint.

IT leaders (and end users) would like AI to not be used for ‘ethical and legal decision making’. This is one of the few areas where the final call should always be taken by a human.

Other popular responses were ‘people management’ and ‘customer relationship management’. ‘Handling customer data’ and ‘handling sensitive business data or IP’ were next in line, tied at number 4.

I reckon AI will evolve to address common data security concerns – a lot better than humans currently can – and specialized AI will emerge that will become essential for CISOs.

6. End-user satisfaction and adoption

Insight: 75% of end-users already use free AI tools like ChatGPT. On a different note, email and phone calls are currently the most popular channels to contact support (26% and 25%, respectively).

Action: Avoid building in a silo and springing the tech to users. Work with end users to solve their problems.

If you’re expecting people to change their behavior, especially in an AI context, your core operating principle needs to be “pander to their inherent laziness”.

Thanks to ChatGPT, DALL-E, and others, your users are comfortable with the idea of using AI – sadly, more than you would have wanted. That might not guarantee adoption, though. If you build (or buy) a multi-million dollar product and employees still call IT for support, you’re not optimizing the return on that investment.

Before launching the AI tech to users, have a deliberate plan for change management – not the ITSM process, but more organizational. An underrated tip is to be friends with your next-door neighbors, HR.

If you’re planning an AI initiative that impacts all employees, like getting a new ITSM software, collaborate with the HR person who is great at generating buzz and getting everyone excited about things.

Chances are, they’re more strategic than you give them credit for.

Closing thoughts

The pressure to adopt AI is already mounting up on IT leaders – from boardroom conversations to requests from end users. SaaS made 'Shadow IT' reasonably easy. But ChatGPT has taken "Shadow AI" to a whole new level. The sooner you plan and get started with AI adoption in IT, the better.

As you navigate the AI landscape, I hope these insights offer a roadmap for informed decision-making and strategic planning.

Download the full report to access more of these trends and equip your team for success in the AI-driven future.