To continue to help drive digital transformations, 97% of enterprise IT and operations leaders say they are increasing AI spending at least through the end of 2025, a new survey finds. But to succeed, much more work needs to be done.
“The introduction of AI is already impacting organizations in the way they operate, with some embracing it enthusiastically,” says Bob Brauer, Founder and CEO of Interzoid, a data usability consultancy and generative AI-powered data quality provider. “However, we’ve only begun to explore its full potential on workplaces, team dynamics, productivity and potential challenges. As these techniques become more mainstream, we can expect even wider adoption and potentially universal applicability,” Brauer adds.
Ambuj Kumar, CEO and co-founder at AI-driven security platform provider Simbian says most enterprises are experimenting with using Generative AI, with the highest ROI and adoption in areas such as programming, with a majority of developers now leveraging GitHub Co-pilot, or ChatGPT, to accelerate coding as well as meeting and longform text summarization, image creation and drafting text. “Finally, scaling out customer engagement with chatbots for inquiries on website or customer support, [and] automatic personalized follow-ups with sales prospects.”
Much of the AI investment focus has been to transform internal processes. For instance, while 32% of respondents to Celigo’s AI Trends in IT and Operations Report said that they are making AI investments into their marketing automation efforts, a higher percentage of companies are making such investments to improve other internal capabilities such as data processing (51%), analytics (52%) and IT services (59%). Additionally, 54% of respondents said that they’re currently using AI for data analysis and insights across their business, while 39% for training and simulation and 38% rely on it to streamline operations.
AI Security and Knowledgeable Staff Top Deployment Challenges
Not surprisingly, the ability to secure AI weighs as a heavy concern for most enterprises, with 56% of respondents citing security as the biggest challenge to widespread AI adoption within their organization. Lack of awareness of useful AI use cases was also a barrier among 47% of respondents, while nearly the same amount is afraid that they’ll lose their job to AI.
When it came to enterprise data integration capabilities among applications, 52% of respondents cited data collection and SaaS application integration as the most significant challenge to building workflows and training AI.
According to a separate survey conducted by IT orchestration and automation solutions provider Stonebridge, the growth of GenAI depends upon effective levels of automation being in place, and 72% of the respondents to its survey said they are using data and machine learning pipelines to fuel their GenAI efforts; while a lack of expertise and staff is the biggest challenge those respondents face when it comes to their GenAI deployments.
However, Ariel Gesto, CEO and founder at service and IT management provider InvGate says organizations are busily putting the capabilities they need to build out their AIOps initiatives in place. “Many enterprises are ramping up their AIOps capabilities. They see the tremendous potential AI has to streamline operations and boost overall efficiency,” says Gesto. “As businesses face increasingly complex IT environments, embracing AIOps is becoming essential for maintaining operational resilience and staying ahead of the curve.”
“It’s also crucial to have a clear strategy and governance framework to ensure your AI initiatives align with your business goals,” adds Gesto. “Some companies are still building these foundations, which means investing in better data management, upskilling their teams, and setting up strong governance policies to oversee AI deployment.”
