For retailers, using AI well is not just a technology decision. It also depends on people who can ask the right questions, judge the answers and take responsibility for what happens next. That is the central argument Nora Gomez, founder and CEO of Next Generation Growth (NGGrowth), makes in a TWICE interview published October 1, 2026.
What does “Human Intelligence” mean in the age of AI?
Gomez defines Human Intelligence as “the leadership capability that enables organizations to turn artificial intelligence into better decisions, stronger execution, and meaningful business outcomes.” In her framework, it means human judgment, clarity, trust and adaptability working alongside AI—not competing with it.
Her point is that AI can produce answers, but people still have to decide which questions matter, whether an answer makes sense and what action to take. “AI is making answers abundant. That makes the quality of the question, the judgment applied to the answer, and the decision about what to do next even more valuable,” she says in the interview with Tony Monteleone.
Gomez also emphasizes accountability: “AI doesn’t remove accountability. A leader still has to make the call.” This is her leadership perspective, not a claim tested by an independent study; the interview provides no statistics measuring its effect on retail performance.
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How can retailers use AI without losing the human touch?
Gomez recommends starting with a business problem rather than choosing a tool first. Retailers should ask where decisions are slow or poor and why, then consider whether AI can address the underlying cause. Automating an unclear process may speed it up without making its outcome better.
She describes AI as an amplifier: it may accelerate learning and experimentation in a healthy organization, but it can also automate existing dysfunction in a troubled one. That is Gomez’s framing, not a measured finding in the interview.
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Her practical distinction is between routine friction that technology can reduce and consequential moments when customers may need expertise or reassurance:
| Customer need | Examples from Gomez | Retail consideration |
|---|---|---|
| Routine and repeatable | Checking delivery status or placing routine reorders | Automation can reduce friction when the customer’s need is straightforward. |
| High-consequence or uncertain | Buying a major appliance or home-theater system | Expert help and reassurance may matter to a customer making a significant purchase. |
The distinction is not that every purchase in one category must be handled by a person. It is that retailers should consider whether automation is removing a needless task or removing help at a moment when confidence matters. Gomez puts it this way: “The goal shouldn’t be to preserve human interaction everywhere. It should be to use technology to eliminate friction so your people can be exceptional in the moments where being human creates real value.”
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Gomez argues that knowledgeable associates can help differentiate a retailer when products, prices and delivery options are similar. For a customer weighing a major appliance or home-theater purchase, an associate who understands the need and can explain choices may help build confidence.
That makes the role of AI more nuanced than simply replacing or preserving every interaction. Used well, it can give employees useful information or free them from routine tasks; the retailer still has to decide where customers benefit from human guidance. The interview offers examples and advice, but does not quantify customer loyalty, sales results or the effect of AI on service quality.
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Will AI replace retail workers?
Gomez’s interview does not forecast job losses, staffing levels or which retail roles AI might replace. It therefore cannot establish whether AI will reduce employment in retail. Her argument is instead about how leaders choose to use the technology and where human expertise continues to matter to customers.
For retailers, the practical question raised by her examples is which tasks are routine enough to automate and which customer situations still call for an employee’s judgment, explanation or reassurance. The interview does not provide a numerical threshold or a staffing formula for making that decision.
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What should retail employees learn as AI improves?
Gomez advises employees to learn how to use AI while also strengthening the capabilities that help them make good use of it. Her recommendations include:
- Build judgment: assess AI-generated answers rather than treating them as decisions.
- Practice curiosity: ask useful questions and investigate what customers actually need.
- Develop adaptability: stay ready to learn as tools and workflows change.
- Strengthen relationships and communication, especially in situations where customers need confidence or expert guidance.
For leaders, the implication is to develop those human capabilities alongside technical adoption. Gomez’s concise formulation is: “AI shouldn’t just make work faster. It should make people better.”
What does NGGrowth offer?
NGGrowth describes its Human Intelligence Index as assessing six dimensions: Clarity, Alignment, Capacity, Culture, Execution and Future Fluency. It describes the Human Intelligence Method as a four-part process: Calibrate, Integrate, Elevate and Accelerate. The company also lists executive advisory, leadership training, fractional executive leadership and keynote experiences. These are NGGrowth’s descriptions of its own framework and services, not independent evaluations of their outcomes. More information is available on the NGGrowth website.
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