In the race to scale artificial intelligence across industries, one challenge consistently stands in the way: Building trust. Organizations are not only expected to adopt AI faster, but to do so in a way that is reliable, secure, and aligned with real business needs. Without that foundation of confidence, even the most advanced technologies struggle to move beyond experimentation.
One of the most effective ways to bridge this gap is deceptively simple: use the technology internally before bringing it to market. By becoming their own first users, companies can validate performance, identify blind spots, and refine solutions in real-world conditions. This approach transforms employees into active contributors to innovation, while ensuring that products are not only technically sound, but operationally relevant.
OpenText offers a compelling example of this model in action. By integrating its own AI and enterprise solutions across the organization, the company has accelerated adoption, improved product quality, and strengthened trust—both internally and with clients. Beyond its immediate impact, this approach also points to a broader opportunity: building a sovereign, high-performing, and trusted AI ecosystem in Canada, capable of supporting businesses at scale.
From Complexity to Clarity: Why Internal Adoption Became a Strategic Imperative
For 35 years, Waterloo-based OpenText has been building robust solutions to support informed decision-making for governments, banks, and major enterprises in over 180 countries. Until very recently, the enterprise had been operating in a highly complex technological environment, with more than 1,600 tools and platforms in use across the organization, reflecting years of growth, acquisitions, and layered systems.
While this ecosystem supported the company’s scale, it also introduced fragmentation, rising vendor costs, and increasing challenges in integrating and maintaining coherent operations.
Rather than continuing to operate within this fragmented environment, OpenText made a strategic decision: to align its internal operations with the very solutions it offers to its customers. Internal adoption became a lever to regain control, streamline operations, and create a coherent technological backbone capable of supporting future innovation.
Becoming “Customer Zero”: A Model for Accelerating AI Adoption
Building on this need for simplification, OpenText formalized its approach through the “OpenText Trusts OpenText” program, an initiative committed to running the business on its own technologies. This marked a shift from isolated internal testing to a structured, organization-wide model where the company operates as its own first customer.
By becoming “customer zero,” OpenText embeds its solutions directly into real operational environments, where they are tested against the full complexity of day-to-day business activities. This approach goes beyond traditional testing methods, exposing tools to real users, real constraints, and real expectations. Employees play a central role in this model. They’re not passive users, but active contributors who identify gaps, validate performance, and provide continuous feedback to product teams.
“ OpenText solutions solve many business problems that every industry is facing. Whether it be how you organize and protect your data, offer employee service management, support the SDLC lifecycle, or offer 2FA to secure corporate devices, OpenText has the solution. By being Customer Zero, we get to provide real-life feedback based on real-life problems we’re solving that are universal to any industry. It’s so rewarding to be able to help create the best solutions, knowing that what works for us helps every over client using our products.“ - Lise Lefaive, SVP, Strategy, Integration, and Operations & CDO at OpenText
Importantly, this transformation is carefully managed. Rather than deploying new tools across the organization all at once, OpenText adopts a cohort-based approach, introducing solutions to targeted groups of early adopters before scaling more broadly. This phased rollout enables the organization to build trust incrementally, refine products based on real usage, and ensure that adoption is grounded in validated outcomes. In doing so, OpenText demonstrates that accelerating AI adoption is—more than anything else—about embedding technology in a way that users understand, trust, and integrate into their daily work.
From Experimentation to Impact: Measuring the Real Value of Internal AI Adoption
The value of internal adoption becomes clear when technology moves from experimentation into daily operations. At OpenText, this shift has driven tangible improvements across the organization, showing how trust and performance evolve together in real-world use.
A clear example is the consolidation of enterprise service management. Previously fragmented across IT, HR, and finance, help desk systems were unified into a single platform, reducing inefficiencies and improving the employee experience. Routine requests dropped by 30%, and with the introduction of AI-powered tools through the Aviator suite, reductions reached up to 70%. These results were not driven by AI alone, but by a structured approach aimed at simplifying processes and ensuring data quality before introducing automation.
Internal deployment also acts as a safeguard. Early use of an identity management tool revealed usability issues, allowing teams to refine the solution before broader rollout. This ability to detect and resolve issues early reinforces internal adoption as both an accelerator and a risk mitigation mechanism.
The impact is also measurable at scale. Internal product adoption has tripled, projected cost savings have reached $1.5 billion over the next 10 years, and major system incidents have decreased by 16%. At the same time, a deeper transformation is taking place: employees become active contributors, continuously improving tools through real-world use.
Ultimately, trust emerges as both measurable and experiential. Organizations that embed this dynamic internally are better positioned to scale AI effectively and turn adoption into a lasting competitive advantage.
Scaling AI the Right Way: A Canadian Imperative
As AI continues to reshape industries, trust is a prerequisite for scaling it and for maintaining our leadership as a middle power. Companies that embed their solutions internally, test them rigorously, and evolve them through real-world use are not only building better technological products, they are also setting a new standard for responsible and effective AI adoption.
For Canada, this represents more than a best practice; it is a strategic differentiator. Strengthening our position as a global leader in AI will depend on our ability to develop technologies that are not only innovative but trusted, secure, and grounded in the realities of our industries. By fostering an ecosystem where companies build and adopt homegrown AI solutions, we can accelerate the adoption and development of technology while reinforcing confidence in Canadian-built solutions.
OpenText’s approach offers a compelling model. It reflects a broader reality faced by many organizations navigating digital transformation, and points to a clear path forward: building AI that is not only powerful, but proven, trusted, and designed to scale from within.
About OpenText
OpenText™ is a leading Cloud and AI company that provides organizations around the world with a comprehensive suite of Business AI, Business Clouds, and Business Technology. We help organizations grow, innovate, become more efficient and effective, and do so in a trusted and secure way – through Information Management.
