Many businesses are adopting AI to accelerate innovation and boost competitiveness. But poor implementation and inadequate governance slow progress and leave organizations exposed to significant risks, like data failures, compliance breaches, security gaps, and reputational damage.
A new Forrester Consulting study, commissioned by Tines, surveyed 400+ IT leaders across North America and Europe to learn more about the challenges and opportunities they’re facing when scaling AI. It found that governance and privacy are the top priorities when it comes to scaling AI – but they also represent the biggest blockers.
The answer? AI orchestration, which connects systems, tools, and teams to ensure that AI runs securely, transparently, and compliantly. Without it, 88% of IT leaders say AI adoption remains fragmented and difficult to scale.
According to 86% of respondents, IT is uniquely positioned to take this strategic role in orchestrating AI. But to make organization-wide impact, they need to overcome silos, align teams, and build trust with a compliance-first AI approach.
Key barriers to scaling AI
Today, organizations face a range of challenges when it comes to scaling AI:
Challenge 1: Governance and security
Businesses are increasingly aware of the risks associated with unchecked AI adoption, and ensuring AI solutions comply with governance and security regulations is the number-one priority for teams over the next 12 months. But traditional governance processes weren’t designed with AI’s complexity and evolving regulations in mind, making governance and security concerns a significant blocker to scaling AI for over a third of teams (38%).
Challenge 2: Trust and transparency
Forty percent of respondents say that employees don’t fully trust the outcomes generated by AI, making it a critical barrier to adoption. Without trust, employees can’t unlock the full benefits of AI, reducing ROI from your AI initiatives and stalling progress towards business goals. Transparency is essential to build this trust, but siloed AI initiatives and fragmented tools make it difficult to foster across systems and departments.
Challenge 3: Organizational barriers
IT is best-placed to scale AI, but organizational perceptions are holding them back. Some 38% of respondents believe that other departments frequently or occasionally underestimate the potential of IT, with 40% citing IT’s reactive focus on troubleshooting and uptime as the primary reason it’s not seen as a strategic driver at the board level.
The solution: unifying people, processes, and technology with orchestration
It’s clear that to overcome these challenges, organizations need to connect systems for greater visibility, control, and effectiveness. As organizations scale AI, almost two-thirds (73%) of respondents highlight the need for end-to-end visibility across AI workflows and systems. Almost half (49%) are looking for partners that can provide end-to-end centralized solutions, which will enable them to reduce siloes and build trust.
Orchestration is the missing link, enabling teams to scale AI with governance, compliance, and security. Without it, IT leaders say transparency is harder to achieve. That leaves organizations exposed to security risks, compliance issues, inconsistent governance, shadow IT, and employee distrust of AI outcomes.
IT is uniquely able to connect strategy, teams, and data through orchestration while maintaining robust compliance, security, and governance. And IT leaders are ready: 38% believe that IT should own and lead AI orchestration, while 28% say it should act as the coordination hub between different business functions.
Elevating IT’s strategic role with orchestration
To effectively orchestrate AI across the enterprise and strengthen their strategic influence, IT teams should:
- Ensure visibility into AI efforts: 51% cite greater visibility across departments as the top factor that would help their IT organization take a leadership role in orchestrating AI across the business.
- Align teams around unified strategies: 49% of respondents say competing priorities between IT and other business teams is the most common factor slowing down or blocking orchestration, revealing the need for strong collaboration and alignment.
- Implement low-code and no-code solutions: 46% report that overreliance on developers or specialists creates a significant bottleneck, highlighting the need for sustainable resource models that leverage low- or no-code AI and automation tools.
- Connect outcomes to business value: 35% say lack of budget or executive sponsorship prevents scaling AI, so IT should frame initiatives in terms of ROI, revenue opportunities, and efficiency gains to secure buy-in and prove impact.
Learn more about how IT teams can lead AI orchestration and drive innovation in the full study: Unlocking AI’s Full Value: How IT Orchestrates Secure, Scalable Innovation.
