Every so often, new technology hits like an earthquake. It starts with faint rumblings, then suddenly creates an irreversible shift in the landscape.
Social media was one of those moments. What began as an experiment quickly became a cultural engine, reshaping how we communicate, consume information and do business. Its promise of connection was compelling, but the guardrails never kept pace. The result is now a system that’s profitable, yet also widely associated with distorted realities, polarization and mental health concerns – especially among youth.
AI is a disruption of an even greater magnitude. In just a few years, it has begun redefining how we work, create and compete. But unlike social media, we still have a narrow window to build what we lacked before: the guardrails that ensure innovation and responsibility move in lockstep.
Those guardrails hinge on two imperatives: trust and talent. Together, they form the foundation for AI that not only avoids past mistakes but also drives responsible AI adoption and meaningful, measurable ROI.
Trust: The currency of AI ROI
Deloitte forecasts nearly $100 billion will be invested in AI compute in 2026. But capital alone doesn’t generate value. In the AI economy, trust is the currency that determines whether those investments translate into ROI. Without trust, even the most powerful AI algorithms will underdeliver.
SAS’ Data and AI Impact Report reinforces this reality, revealing what we call the trust dilemma: the gap between how trustworthy organizations believe their AI is and how responsibly it’s implemented. The larger the gap, the lower the ROI.
Yet many companies are leaving value on the table. Only one in four organizations have a dedicated team overseeing AI ethics, fairness, data quality and bias detection. As a result, many are deploying increasingly influential AI systems without the foundation to ensure they’re trustworthy. Given AI’s propensity for errors, hallucinations and other misleading outputs, that’s not just a technical oversight – it’s a liability.
The first step in building trustworthy, responsible AI is to focus on its fuel: data. Strong, centralized data is critical to successful AI adoption. Since 2024, data centralization has risen from the seventh-largest challenge to the top obstacle in deploying AI effectively.
The right data foundation is a differentiator. It ensures responsible AI while driving innovation, efficiency and measurable value.
Building trust in AI isn’t a constraint; it’s a catalyst for scale and ROI.
Talent transforms AI risk to advantage
Trust in AI does not emerge from technology alone; it’s realized through skilled professionals who understand both AI and ethics.
Even the most sophisticated models can become sources of risk without people capable of interpreting outputs, identifying bias and ensuring alignment with organizational and societal values.
SAS’ Data and AI Impact Report underscores the human dimension of these challenges: 62% of respondents worry about data privacy, 57% about transparency and 56% about ethical use.
As AI becomes more autonomous through agentic AI, organizations are increasingly responsible for governing its actions. Competitive advantage comes from pairing AI with the right expertise: People who know when oversight is essential, when errors are costly and where AI can safely accelerate workflows.
This need is especially pressing in the context of digital sovereignty. In 2026, nearly US$100 billion will be invested globally in sovereign AI compute. Organizations may be required to cultivate local talent to ensure compliance, ethical alignment and contextual decision-making. Trust in this local expertise becomes necessary to allow companies to navigate sovereignty challenges effectively
Programs like the SAS Talent Connection help meet this need, equipping emerging professionals with skills to go beyond coding and analytics and to understand how to build and deploy AI responsibly.
Human expertise transforms governance frameworks and technical controls into actionable safeguards, turning potential risk into a competitive advantage.
Building a future we can trust
The rumblings are already here: AI is transforming how we work and challenging long-standing norms. But this is just the beginning. And now is the time to build the guardrails of trust and talent.
By embedding responsible AI into systems and investing in people, organizations can turn potential disruption into opportunity.
Those who build strong data foundations, cultivate talent and prioritize trust will gain more than compliance – they will achieve measurable ROI, sustainable innovation and a future that we can trust.
