AI adoption is more than a technical transformation, and organizations have been underestimating the human side of AI implementation, including employee fears, organizational culture, communication breakdowns, and trust.
The human angle of AI adoption for organizations was a major talking point during SAS Innovate 2026.
At the conference, Channel Insider sat down with both Kristi Boyd, Senior Trustworthy AI Specialist at SAS, and Gavin Day, Executive Vice President and Chief Operating Officer (COO) at SAS, to discuss the human side of AI implementation and the gap between AI investment and measurable returns.
The importance of organizational culture in successful AI deployment
Both Boyd and Day emphasize that organizations often underestimate the human side of AI implementation – including employee fears, organizational culture, communication breakdowns, and trust.
Boyd argues that successful AI adoption depends on understanding why employees may resist AI and addressing those concerns directly. Oftentimes, organizations will deploy AI everywhere without clearly understanding its value, which can impact employee trust.
“A lot of innovation we look at, we see a curve where something happens – insane growth in adoption – and then we realize we don’t actually need everything to be on the internet,” Boyd explains. “We don’t need everything to be digitized. I don’t need my toothbrush to have AI, right? So, then we see that curve break up as we realize where the actual value is.”
Employees need to buy into AI adoption, not fear it
According to Boyd, the conversation about culture has never been more significant than it is today.
Enterprises need their employees to buy into adoption processes and new technology; otherwise, they are force-feeding it to them without explaining the actual impacts and what it means for the future.
“I think when we think of adoption – scale especially – we need to figure out what the hesitations are for folks,” said Boyd. “And there’s going to be different approaches to different reasons for it.”
“Some of those reasons are really valid,” she adds. “There’s historically been instances of discrimination, right? So, there’s a lot of fears before – are we going to repeat the same thing that’s happened in the past? There’s fear of ‘is my job going to get replaced, and how am I going to provide for my family?’ Those are concerns.”
Women face a higher impact on their career potential as AI expands
According to a recent report from the National Partnership for Women and Families, women make up 47 percent of the workforce but comprise 83 percent of those employed in AI-vulnerable occupations.
Further, the study notes that women of color make up 31 percent of workers in the 15 most AI-vulnerable jobs.
Boyd highlighted the wide range of emotional responses to AI adoption that companies can’t ignore, regardless of industry. Concerns around fairness, historical discrimination, and job displacement are valid organizational concerns rather than irrational fears, Boyd said.
Trustworthy AI and AI governance
Day, meanwhile, highlighted the tension between innovation speed and the deployment of trustworthy AI.
While generative AI appears to accelerate productivity, enterprise use cases require precision, accountability, and governance.
“Generative AI has proven personal productivity – I use it every day,” Day said. “But it lacks precision. If you ask an LLM the same question 10 times, you’re not going to get the same answer 10 times.”
He added that “if we’re thinking about money laundering or credit card fraud, where precision is critical, that’s where SAS is a trusted adult in the room.”
Boyd spoke about a four-pillar framework for AI governance:
- Oversight
- Compliance
- Operations
- Culture
The framework is presented as a roadmap for organizational AI maturity.
Centralized governance tools help organizations understand where AI is being used, by whom, and for what purposes, Boyd explains.
“SAS Navigator really provides that visibility across the entire ecosystem of the organization,” said Boyd. “What we want to do is make it easy for organizations to say, ‘Hey, HR is using this tool from this one vendor. Turns out folks in IT are also using something similar from another vendor. Can we marry them? Can we have a conversation across departments to have that visibility?’”
Open AI ecosystems and enterprise flexibility
These days, enterprise AI infrastructure is evolving toward openness and interoperability, according to Day.
Rather than forcing customers into a single ecosystem, SAS is enabling organizations to run AI workloads across multiple environments and to use the models and languages they already depend on.
“For us, it’s one of the core tenets – you can run it anywhere. That was a design choice,” Day told Channel Insider. “We continued to make sure that we supported the same code base on-prem, hypercloud, public cloud, and private cloud.”
He adds that the third leg of that stool is that organizations can bring their own tooling, with SAS supporting whatever LLM they choose.
Why channel partners are more important to the IT ecosystem than ever before
Partner ecosystems are becoming increasingly important to scaling enterprise AI solutions globally.
Rather than operating independently, SAS increasingly relies on channel partners, resellers, and systems integrators to extend its reach.
“Partners are critical for our success. Partners are experts in areas where we’re not, so for us to empower their businesses and make their customers successful is incredibly important,” said Day.
Scaling AI and the enterprise AI reality
Boyd warns that organizations often attempt to scale AI initiatives without first establishing centralized governance and operational systems, creating fragmentation and inefficiency.
“Right now, it’s emails, it’s work docs that people put together, it’s a presentation somewhere in PowerPoint – that’s not scalable,” Boyd said. “You need something centralized to scale. Otherwise, you’re just scaling chaos, right?”
There’s a disconnect between AI investment levels and measurable enterprise outcomes.
Day says that organizations are spending heavily on AI, but many still struggle to identify concrete returns on investment.
“There’s tremendous amounts of money being spent. I was reminded of a quote I heard last year – it was the ‘summer of disappointment’ around AI,” said Day. “I still think we’re there a little bit because of the money being spent. When I sit with executives and customers, I talk to them about a measurable problem that they need to solve.”
Channel Insider also spoke with SAS’s Senior VP, Global Channels, John Carey, at the conference. Read more about how SAS is strengthening its partnerships while positioning itself around human-centric, responsible AI.
