Generative AI: How to Use It the Right Way - An Interview with Dr. Cindy Gordon
Nicholas Page
·
3 minute read
The promise and the pitfalls of generative AI
Generative AI is hailed as the next major wave of digital transformation. But according to Dr. Cindy Gordon, while the potential is huge, the ROI is currently hovering at a mere 5% globally. Why? Because most businesses are diving in without due diligence.
In this episode of Tech Marketing Trends, Dr. Cindy Gordon is interviewed by Jakob Löwenbrand to explore how companies can embrace generative AI responsibly, avoiding hype while focusing on strategy, governance, and real business impact.
“There’s tremendous hype, tremendous hope—but also real risks. We’re only seeing a 5% return on investment globally for generative AI.” – Dr. Cindy Gordon
Gordon emphasizes the need to approach generative AI with strategic caution, especially in sales and marketing organizations where it’s often misapplied or misunderstood.
Start inside: internal use cases first
Before jumping into customer-facing applications, Gordon recommends starting with internal operations like call center automation, predictive analytics, and software development enhancements. These use cases are lower-risk and allow teams to build competency in a more controlled environment.
“Start internally, not externally. Call centers, predictive analytics, software development—these are safer, high-return entry points.”
If you're rethinking how you enable your internal sales pipeline, Brightvision’s lead generation services can help build the right foundation before layering on AI.
The risks you didn’t hear about
Gordon doesn’t shy away from pointing out AI’s darker corners: hallucinations, model implosions, and even deceptive behavior from certain large language models (LLMs). She warns that many users don’t realize these systems can purposely withhold the truth.
“These models can lie. They have a self-preservation logic and sometimes hide the truth. That’s a big risk.”
This makes the case for responsible AI governance with policy frameworks, ethical audits, and defined leadership accountability from day one.
Governance is not optional
With no unified international regulatory standard, the responsibility for safe AI usage falls squarely on companies. Gordon refers to the Paris AI Safety Summit, noting that neither the US nor UK signed its accord—underscoring the fragmented landscape.
“Have strong governance. Even mid-sized companies need ethical AI policies and technical audit trails.”
When AI becomes part of your go-to-market approach, it should align with your overall vision and be as considered as your marketing strategy.
From open source to smaller LLMs: smarter tech choices
With large vendors becoming increasingly complex and opaque, many enterprises are turning to open-source models and smaller domain-specific LLMs that are more manageable and efficient.
“We’ll see a rise in smaller LLMs that are more environmentally friendly and fit narrow use cases—especially in sales and marketing.”
These compact models are often more transparent and better suited to typical B2B workflows.
Where AI is already delivering value
Gordon provides several proven use cases where AI is already having a measurable impact:
- Predictive analytics at the top of the funnel with up to 95% accuracy
- Sentiment mining and happiness tracking in sales forecasting
- AI agents in call centers delivering faster and more accurate support
- Low-code tools accelerating software development cycles
Still, she warns that contextual understanding is not yet mature in many tools.
“Even when you get insights, people still ask, ‘Why am I being told this?’ Human context and experience still matter.”
Jobs of the future: what's in and what’s out
Some roles, such as BDRs, are being partially replaced by automation. Meanwhile, demand is growing for AI prompt engineers, experience designers, and AI ethicists.
“Marketing professionals need to be more creative. Think avatars, event marketing, and storytelling in immersive formats.”
Gordon also encourages marketers to explore customer experience design and creative writing—skills that algorithms can’t easily replace.
Cautionary advice for AI newcomers
When discussing what not to do, Gordon reframes the focus toward what should be done:
- Avoid hype-led decision making
- Anchor every AI use case to business strategy
- Be aware of vendor lock-in
- Understand where tech giants like Microsoft and Google are placing bets—and why
“Pick your spots wisely. Many companies are picking the wrong ones right now.”
Final thoughts: AI is reflecting us—flaws and all
Perhaps the most sobering takeaway is Gordon’s warning that generative AI models often reflect the same flaws found in human behavior.
“Humans are deceptive. If we train AI on human history, it will learn deception too. That’s why we need models that monitor other models.”
With new tools emerging that evaluate AI’s truthfulness, Gordon sees a future where even AI must be held accountable—by other AI.
Want to learn more?
You can explore Dr. Gordon’s ongoing thought leadership through her weekly AI Insights on LinkedIn, her writing on Forbes, and her upcoming book on AI governance.
For more episodes like this, check out Brightvision’s podcast library, or contact us to learn how we help B2B companies future-proof their marketing with AI-driven strategies.
