Throughout history, the ambition of technological advancement has always been driven by the pursuit of human prosperity. But with AI, we are approaching a pivotal gut check to live up to this promise for the next generation.
In my role as CTO at SAS, I talk with a lot of organizations about the future of technology, spanning AI adoption, workforce impact and practical governance. Keeping an open dialogue is important, not only because we need to understand all the nuances of AI, but also because we’re using it to reshape how we live and work – and we need to do it the right way.
I’ll share some of the questions I’ve been getting from other technology and business leaders, along with my answers.
Why do I need AI?
Every day, there is a widening gap between the volume of data created and the capacity for humans to consume and make sense of it. This information overload is creating both fatigue and opportunity. Companies that learn faster in this data-intense environment gain a competitive advantage. However, companies are built on employees and technology. AI is a breakthrough innovation that enables us to further scale human observation and decision-making – and close the information gap.
How do you define success with AI?
Always start with the problem you’re trying to solve before thinking about which technology you need. This is a time-tested strategy. The right technology is the one that solves your business challenges. For example, generative AI’s strength is in reasoning across unstructured data, but its weakness is in quantitative analysis. That’s why a full AI stack is required, including machine learning for quantitative analysis, generative AI for natural language interactions, and an architecture that orchestrates it all. But, I am also seeing many organizations repurpose AI budget to perform long-overdue automation when AI is not needed at all. Simply put, you should let the problem lead you to the right technology, which in turn drives a successful business outcome.
Will agentic AI go away as large language model context windows get larger?
Infinite context windows don’t seem to be the answer. They might help, but there are diminishing returns because, at some point, the ability to navigate generalized models for a specific task gets more complicated. The workflow of agentic AI consists of understanding the goal of the user, developing a plan of discreet tasks, orchestrating tools to fulfill these tasks, evaluating the results, and responding. The large language model (LLM) plays an important role, but it’s just one technology in the larger orchestration needed to deliver a trusted decision with agentic AI.
How important is governance when it comes to trust and responsible AI?
As I said earlier, companies that learn faster in their industries gain a competitive advantage. But, companies are built on employees and technology, and AI is a critical technology to scale the learning rate of employees. Strong AI governance provides the needed guardrails for employees to learn faster, scale impact and minimize risk to businesses and customers. And this isn’t just my opinion. A recent IDC report commissioned by SAS confirmed that organizations focusing on governance, explainability and ethical safeguards – which are all foundations of building trust – realized greater ROI from AI initiatives.
What is the new role of the employee in the age of AI?
Since the beginning of the information age, employees have followed the 80/20 principle for analysis. They spent 80% of their time collecting and organizing data, and only 20% of their time analyzing it. For the first time in history, we have a chance to flip this ratio with AI. This means the new role of the employee is to develop critical thinking skills to ensure results from AI are accurate, aligned with business goals, and avoid unintended consequences. This also means leaders must create psychological safety for the debate of AI-assisted answers. Over time, the employee’s role ultimately shifts from data curation to verification.
Can you make one bold prediction for the AI market in 2026?
Many companies will leverage AI to cut their workforce. Why? Because it is the easiest and quickest path to ROI from AI. However, this short-sighted approach hinders future business growth. There is no question that AI will impact the nature of jobs, but the world needs bold and inspirational leaders to invest in their workforce through this continued change. The same IDC report found organizations that focus on customer experience, market share and resilience as primary AI goals report higher ROI compared to those that focus simply on cost reduction. When we empower people with AI – instead of displacing them to cut costs – we free up their time to work on higher value problems, drive new revenue growth, and gain a competitive advantage for their business.
As I said at the beginning, the ambition of technological advancement has always been driven by the pursuit of human prosperity. Let’s keep that promise.
