Over 90% of enterprises are currently experiencing limitations integrating AI into their tech stack, according to new research released by Tray.io, creator of the AI-powered, multi-experience iPaaS. Almost three quarters of companies (73%) report that more than half of the apps in their tech stack have AI capabilities or AI-augmented features, and 96% plan to use these features to improve process efficiency and employee productivity, increase customer satisfaction rates and reduce costs. However, this rapid proliferation of AI within existing SaaS apps is causing significant integration pains, including challenges with provisioning and on-going management, lack of AI implementation frameworks and issues surrounding change management within the organization. Further complicating the issue, there is a stark disconnect between executives and practitioners in regards to AI implementation strategies. Almost half of enterprise executives (48%) indicate that their organization's AI implementation strategy for the next year is focused on building strong integrations between their internal SaaS apps and AI, while close to 20% of practitioners state their organization doesn't have an AI strategy as it relates to their tech stack and internal business processes.

With Businesses Swimming in a Sea of SaaS, Lack of Clear and Aligned AI Integration Strategies Could Hinder Progress

Organizations face a tech stack doomsday as the wave of AI-enabled SaaS apps threatens progress. SaaS bloat remains a challenge with 55% of companies reporting that they have more than 50 SaaS apps in their tech stack and 37% stating they have more than 100. Compounding this issue, most apps now offer some sort of AI functionality - 73% of respondents state that more than half of the apps in their tech stack have AI capabilities or AI-augmented features, and 40% of respondents plan to use the built-in AI features for more than half of their SaaS apps. 

"Enterprises embarking on their AI implementation journeys will be challenged with managing the functionality of dozens of different AI features without causing conflicts between connected apps and unifying their technical teams while being careful not to overwhelm them," observed Rich Waldron, CEO and co-founder of Tray.io. "Properly harnessing the power of AI in a safe and effective way requires companies to centralize on a solution built for the age of AI, and use it as the control center where precise decisions can be made about where and how to infuse AI into business processes for the best outcomes."

Moreover, there is a disconnect between the C-suite and practitioners when it comes to AI implementation initiatives. Almost half (48%) of enterprise executives state that their organization's AI implementation strategy for the next 12 months will be focused on building strong integrations between their internal SaaS apps and AI. As part of their AI business process strategy, over half (57%) of executives intend to use the app-specific AI for each SaaS app in their tech stack. In contrast, only 32% of practitioners and team leads state this will be the primary focus for their organization - and almost 20% of practitioners state their organizations don't have an AI strategy as it relates to their tech stack and internal business processes.

"While the Autonomous Enterprise is the desired end state for all organizations, going down the path of implementing the AI features of every SaaS app will undoubtedly lead to a new slew of unintended consequences. To move forward with AI integration in a sustainable way, enterprises will need to centralize on a single platform that simplifies development and ongoing management," continued Waldron.

As businesses work on integrating AI, respondents are currently experiencing significant barriers, including provisioning and ongoing management, a lack of implementation frameworks and difficulties handling change management. Depending on seniority, the top limitations cited are challenges with provisioning and on-going management, change management within the organization, processes being too dependent on developers, lack of implementation frameworks, and AI features being either hard to experiment and prototype with or too costly and time-intensive to integrate. 

While enterprises build out their AI implementation strategies, data governance and employee skill sets are top of mind. When implementing AI, organizations cite managing data governance, compliance, security and trust; lack of familiarity with AI tooling; and lack of workforce skills and access to employees with relevant skill sets as the top three challenges.

Additionally, almost one-third (32%) of executives anticipate encountering employee pushback as they implement AI in the enterprise. 

Enterprises are Optimistic About the Potential of AI to Improve Efficiency, Enhance Productivity and Boost Customer Satisfaction

Despite the difficult road ahead, survey respondents report they are optimistic about the potential impact of AI to revolutionize business operations, with top anticipated benefits cited as improving process efficiency, enhancing employee productivity and boosting customer satisfaction rates. IT is universally identified as the number one practice that can most benefit from the application of AI, followed by Product Development and Engineering and Customer Service and Success.

Across the board, the top three ways respondents plan to personally use AI in their own roles are: 

• Adding AI to improve or enhance internal business processes for themselves and other departments
• Using AI to automate manual work or business processes
• Improving everyday decision-making for their department
  

Respondents indicate that, in the future, they expect AI to enhance their productivity, simplify daily tasks and facilitate faster decision-making, as well as provide templates and frameworks that help them improve their job performance.

"The 2024 AI Implementation Strategies in the Enterprise survey not only sheds light on the current state of AI integration strategies - including the anticipated benefits of AI and expected challenges - but also emphasizes the urgent need for a unified solution to address the impending management challenges companies will face as they integrate AI into their business processes to increase productivity and gain competitive advantage," concluded Waldron.