Trust, Transform, and Transcend: these are the three phases of the T³ model developed by Beta-i to help organizations integrate AI strategically and, to TEK Notícias, Manuel Tânger, co-founder and Head of Future at the collaborative innovation consultancy, explains how it works.
For companies, Artificial Intelligence has the potential to open the door to new opportunities, with productivity gains and greater efficiency in their operations. However, the technology also brings new challenges, including doubts, fears, and uncertainties regarding its implementation. For Beta-i, the answer lies in a new model called T³.
“T³ ends up being a formalization of the observation we’ve had with our clients when we address the topic of AI and want to develop and follow this fast, fervent, giant wave that we are all witnessing,” says Manuel Tânger, co-founder and Head of Future at Beta-i, in an interview with TEK Notícias.
As the executive explains, there isn’t a single company the consultancy speaks with that doesn’t have AI at the top of its agenda. On the other hand, organizations still have very diffuse ideas about how they should adopt the technology. The T³ model was designed to help organizations integrate AI strategically and is composed of three phases: Trust, Transform, and Transcend.
According to Manuel Tânger, “the first phase is one of gaining trust.” Here, “there’s a whole set of difficulties that companies have to overcome,” including uncertainties about how the technology works and compliance issues, in order to “gain literacy through practice and not through reading.”
If the Transform phase envisions a more immediate future, one where AI stops being a support tool to become central to the creation of new solutions, products, and business models, the Transcend phase asserts itself as an even deeper change over a longer period.
In the words of Manuel Tânger, this phase is something more societal, in a “change so deep and systemic” that “our very appreciation of being, of value, of money, of work, of society, of the relationship with the government, of the very notion of the company” will change completely.
For Beta-i, reaching this new framework brought “immense clarity,” says the executive.
“And we’re able to pass this clarity on to clients so they can make this journey,” also helping to calm the “anxiety that exists around AI about what to do and how to do it.”
As he details, currently, the vast majority of organizations are in the Trust phase, meaning they continue doing what they did before, with AI accelerating and improving processes, but still without a major shift in their businesses. But moving from the “business of today” to the “business of tomorrow” remains the big challenge.
Some companies seem to have already reached the Transform phase, but are, in fact, in what Miguel Tânger calls a “sophisticated Trust.” “The difficulty is still in gaining confidence, that is, understanding the limits of what is currently being done with AI,” he highlights. “It’s a learning process, both legal and technological,” in which organizations need not only to “dive in” but also to “move forward with willingness.”
In this context, innovation skills play a central role, because “this is a transformation, it’s a change in mindset, in technology, probably in the business itself,” the executive says. To move forward on this journey, companies need to adopt an experimental approach that allows them to test new solutions without being afraid to learn from mistakes.
“A company that, in the past, already innovated without AI is now in a great place to innovate and transform with AI” he points out. On the other hand, “for those who resist change, and for those who try, fail, and don’t try again, it will be very difficult.”
Regarding the sectors most prepared to make the “leap” and move to the Transform phase, Manuel Tânger says that, interestingly, this is a somewhat “area-agnostic” issue.
“The major differentiator we see that creates the best foundation to make Transform possible is the amount of structured information the company already has – that is, how much of the practical knowledge of operations is already incorporated into information systems,” he states. “If that already exists, it’s a great step.”
This article was originally published in Tek Notícias on Oct 6, 2025