Are IT departments ready to implement AI?

AI-powered tools are transforming all industries, but that doesn’t mean that AI adoption is consistent across all of them. It’s obviously a priority in IT departments, and leaders are ready to adapt to this technology.

Research from our State of IT Lifecycle Management report shows that task automation is the most sought-after AI feature. Almost 60% of respondents say that their organization has plans to implement this feature in 2025, followed by AI-powered reporting and analytics (48%) and AI-powered IT support (39%). 

While there is high enthusiasm for AI adoption, each company’s readiness for implementation varies significantly. Leaders are concerned about adopting the technology fast enough to reap the promising ROI of increased productivity, but IT managers might not be ready to follow suit. 

Yes, the technology is available, but there are still concerns about protecting proprietary data or the budget available for implementation. Even if businesses are ready to invest and have a proper policy, these tools would still have a learning curve.

Organizations can ease into AI adoption by partnering with suppliers and vendors who have already embraced AI-driven solutions. The question remains: Are companies truly operationally ready to implement AI, or are they rushing into investments without the necessary groundwork?

AI-powered automation in IT operations

As industry expert Guillermo Diaz Jr. highlighted in a recent interview with GroWrk, AI’s potential in IT operations lies in its ability to enhance efficiency and intelligence across the IT asset management lifecycle. Companies that successfully implement AI stand to gain a significant competitive advantage.

“The last two years have really been about generative AI, but AI has been around for decades. They all work together conjunctively, but you have to think about how you use it as a productivity tool for yourself, how you use it to automate, and then how you use it to autonomize your enterprise,” Guillermo explains.

"If I’m in IT, I better be thinking about how I scale up and look at what I need to learn that will help me and my organization adopt, accept, and change the mindset of how we move into this new era of AI."

In an industry like IT asset management, many people still use spreadsheets or some form of proprietary data source, but when the CFO or CIO want to know about cost structure, retrieving that information is hard because it requires a lot of manual work on the back end.

Instead, leveraging solutions like GroWrk, which already use AI features, allows users to get insights into their assets at the push of a button. Then, they can show the business that what they invested in is adding value and reaching their ROI target.

Although automation offers promising results for IT operations, our research also suggests that 15% of respondents are still hesitant and will not implement AI features or AI-powered tools by the end of the year. This is likely because bridging the gap between AI potential and operational readiness comes with a few challenges.

How IT teams can overcome AI adoption challenges

One look at Reddit shows that IT managers are not convinced about how companies are rolling out AI tools in the business. Some say there is not enough information or resources available to integrate AI, others point out the lack of budget, and some poke fun at disjointed efforts that violate existing company policy.

In our survey, data privacy (61%), data breaches (41%), and data leakage (41%) were identified as the highest security concerns when using AI tools. Other concerns included reputational damage (24%), insecure API endpoints (22%), impersonation (20%), data manipulation (17%), insider threats (17%), and supply chain attacks (17%).

It's true that AI tools have transformative benefits, but companies must also address the concerns of IT managers when implementing these tools. These concerns include:

• Security and privacy risks: AI tools often process large amounts of sensitive data. Employees who use these tools to complete daily tasks might inadvertently share proprietary information. Companies must follow the IT departments' recommendations to update policies and guidelines to include these new use cases and roll out training to ensure employees understand them.
• Cost vs. benefit: Leaders might want to stay ahead of the curve but underestimate the cost of an enterprise license or push for a novelty product that doesn’t meet their team’s requirements. In any case, IT leaders must analyze their available budget and business needs to determine the financial viability of AI solutions.
• Change management: Adopting AI also requires a cultural shift. IT teams must be prepared to embrace automation and new workflows by providing training sessions and guidance for company-wide teams. 

Companies can work around these challenges by partnering with suppliers or vendors with solid AI-powered platforms. For instance, IT teams can use services like GroWrk, an AI-powered platform that helps procure and manage IT assets worldwide. This way, you automate a whole IT function, like procurement or lifecycle management, through a third party. Plus, GroWrk’s platform is SOC 2 compliant, guaranteeing your data is safe.

Preparing IT professionals for an AI-driven future

As with any new technology, AI requires literacy. Understanding how AI works and its use cases across industries can set apart the innovators from the laggards. 

That’s why training and upskilling should be a core part of the budget allocated to AI implementation and adoption. Leaders in all industries must prepare their workforces to adopt and adapt to new tools and technologies.

IT teams are expected to stay up to date on the latest tech, but they also need resources to develop their skills further. Companies must at least focus on the following areas:

• Supporting employee adaptation: Adaptation is more straightforward when resources and guidelines are available. Organizations should foster a learning culture and incentivize employees to learn about new technologies like AI. Additionally, companies should champion ongoing training regarding company policies on generative AI usage involving the IT department.
• Developing AI skills: On an individual level, professionals across industries should understand AI's potential and use it innovatively. Equally important is taking a hands-on approach and experimenting with different tools.
• Training programs and certifications: Additional training and certifications can help specialized employees, like IT professionals who already know how AI works, level up their skills and fuel innovation.

When generative AI models started to pop up with astonishing capabilities, employees feared being replaced by such models. Now that they have begun to use them as part of their daily workflows, it’s clear that gen AI is not a human replacement but a productivity enhancer. 

As Tim Fernihough, Orium co-founder, mentioned in an interview with us: "AI is not going to take our jobs, but someone who knows how to use it better could. So I think it's about not being afraid of embracing it and understanding how it can make things better both within our tools and the tools that we subscribe to in our own work and how we serve our clients.”

How IT teams can invest in AI growth

Technology spending is often seen as the biggest cost center for many companies. Flexera indicates that almost a quarter of IT leaders spend $10–$25 million on their IT budgets annually, while 19% of them spend $25–$50 million.

Our research shows that 9% of organizations plan to allocate 70-79% of their IT budget to AI, and another 9% anticipate dedicating 80-89% to it.

The challenge for many organizations is to allocate their IT budgets effectively. A well-rounded budget should include investments in infrastructure, security, and employee development. This way, leadership can guarantee that they will be operationally ready to leverage AI tools.

Additionally, companies must train and prepare their workforce to truly reap the benefits of AI tools. Investing in AI technology is necessary, but allocating enough time and financial resources to an AI adoption strategy is equally important.

The first step in creating an AI adoption strategy is identifying the business problems that AI can solve. Companies should also assess their current technology infrastructure and determine whether it can support the new tools. 

While AI is a priority for many companies, they must also be careful not to let their investments in this area compromise other critical IT initiatives.

Once implemented, organizations need to define specific metrics for evaluating AI’s impact, including how much money it saved, areas that showed the most improvement, time savings, and areas of opportunity. Ultimately, these findings can help IT leaders make informed decisions that benefit the business.

Wrapping up

AI is reshaping all industries, promising improvements in automation, decision-making, and predictive analytics. However, even a company willing to invest in the latest AI tools to improve its operations can face significant readiness challenges. Security concerns, cost considerations, and preparing its workforce for change are core directives of AI adoption strategies.

Organizations that take a strategic approach, like leveraging AI-friendly suppliers, investing in training, and carefully planning their budgets, will be better positioned to unlock AI’s full potential. The future of AI in IT operations is bright, but success depends on more than just financial commitment; it requires operational readiness, a skilled workforce, and a clear vision for AI integration.

Experience the benefits of GroWrk’s innovative AI implementations and how they can optimize your IT asset management strategy across 150 countries. Book a demo today.