The Next Steps in the AI Operations Revolution
June 26, 2024

Scott Henderson

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IT and Operations leaders across a range of industries are enthusiastically — and nearly unanimously — on board with artificial intelligence, having already implemented AI solutions and realized early successes. Leaders say AI is essential to the future of their companies and are planning to increase investments in the technology, according to the results of the Celigo iPaaS AI Survey Report.

However, more than 1,200 global enterprise Operations and IT leaders surveyed in May also cited barriers to the widespread, enterprise-wide adoption of AI, identifying several issues they need to address before they can take full advantage of everything AI has to offer.

AI Already Generating Positive Results

The survey results make it clear that organizations are actively pursuing AI's possibilities, with nearly all respondents saying they have adopted AI, and most saying they have seen improvements in areas such as productivity and efficiency (49%), optimized operations (45%), enhanced customer experiences (38%) and reduced costs (37%). Looking forward, IT leaders expect significant further improvements in those areas.

And they are just getting started, with 97% of respondents saying AI is critical to driving operational improvements in the coming year. Most respondents plan to spend at least 25% to 50% more on AI in 2025, and 76% already have dedicated resources and a budget for AI in place. And 82% stated that their organization is already following an AI strategy or roadmap for implementation.

The top areas of AI use include data analysis and insights (53%), customer support (42%), training and simulation (39%) and streamlining operations (38%). Looking forward, respondents said they expect AI to transform all business processes, particularly in IT services (59%), analytics (52%), data processing (51%) and marketing automation (32%).

Clearing the Hurdles to Full Integration

But before their companies can achieve widespread adoption, respondents said they must tackle several issues that are holding them back. For one thing, overburdened IT departments are spread too thin to cover all AI implementations, which is prompting organizations — 53% of them — to allow business users to manage their own solutions, as long as they have proper IT governance. Overall, 68% are willing to embrace a "Citizen Developer" mindset, supporting users who want to automate front- and back-office operations.

Among other hurdles to widespread AI adoption, 56% of respondents cited security concerns, 47% cited a lack of understanding about what AI can do for the organization, 46% said employees fear being replaced by AI and 33% said other IT priorities outweigh the importance of AI.

Leaders also identified technical challenges, such as difficulty integrating SaaS applications enterprise-wide (52%), connecting data across applications (51%) and overall implementation (45%).

A key to overcoming these challenges is a solid, foundational strategy for integrating applications, boosting data collection and providing governance and the guardrails necessary for Citizen Developer involvement, among other things.

A Roadmap to Widespread Adoption of AI

As IT and Operations leaders embark on the next phase of their AI transformation, they should follow an integration roadmap to drive mass adoption of AI across their enterprises. Here are five key steps they should follow:

Create a comprehensive AI strategy that aligns with business goals. The roadmap should include a timeline for implementation and a documented AI policy for the organization that includes both technical and non-technical employees at multiple levels.

The strategy should identify key performance indicators (KPIs) and success metrics to enable measurement of ROI.

Upskill technical and business employees. Organizations need to provide training to both IT teams and business users on AI tools and technologies. Training programs should include a feedback loop, where employees can share their experiences along with regular knowledge-sharing sessions such as "AI Lunch and Learn" or "Tech Talks."

Recognizing employees who actively pursue learning about AI and are applying it to their jobs will help encourage a culture of continuous learning and innovation.

Encourage experimentation with AI technologies. The environment should promote a growth mindset by valuing experimentation and continuous learning. This includes providing employees with access to the latest — secure — AI tools and the resources and infrastructure to enable experimentation. Forums, internal networks and communities of practice can facilitate knowledge sharing and collaboration across departments.

Integrate AI into existing business processes. Organizations should follow a clear path to integrating AI, starting with an inventory to determine which business processes require automation. After prioritizing them accordingly, you should clearly define objectives for AI, monitor the progress of all implementations and seek to optimize AI use. Before a company-wide rollout, pilot a solution with a small group while providing training for all stakeholders.

It's very helpful to use a tool built for integrating solutions and automating tasks, such as an Integration Platform as a Service (iPaaS). And it's important to regularly report on results throughout the integration process.

Integrate AI tools that boost productivity. Organizations need to carefully select the AI tools that will work best for them, automating tasks and supporting faster and better decision-making. Look for solutions that automatically identify and resolve errors in workflows, as well as those that enhance data analysis and decision-making. Those solutions can enhance productivity, efficiency and overall business performance, while reducing operational inefficiencies and helping businesses plan more effectively.

IT and Operations leaders clearly see AI as integral to their companies' future prosperity. And careful planning coupled with a systematic integration strategy can help create an AI culture that will bring its enterprise-wide adoption to fruition.

Scott Henderson is Co-Founder and CTO of Celigo
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