AI Safety Connect in New Delhi: What CX and EX Leaders Must Learn About Trust, Governance, and the Future of AI
Ever launched an AI feature your customers didn’t trust?
Picture this.
Your team rolls out a new AI-powered assistant.
It promises faster resolution and lower costs.
Your board celebrates.
But customers hesitate.
Employees bypass it.
Regulators start asking questions.
Trust breaks before value lands.
Now zoom out.
On 18 February 2026, nearly 250 global leaders gathered in New Delhi at AI Safety Connect (AISC) to address a similar risk—at planetary scale. The convening, co-hosted with the International Association for Safe and Ethical AI and supported by Minderoo Foundation, focused on advancing international AI safety coordination during the India AI Impact Summit.
For CX and EX leaders, this was not a policy event.
It was a warning signal.
Because AI safety is becoming a customer experience issue.
What Is AI Safety and Why Should CX Leaders Care?
AI safety ensures AI systems are reliable, aligned, secure, and trustworthy. Without it, customer trust collapses before ROI materializes.
At the New Delhi convening, Nicolas Miailhe, Co-Founder of AISC, set the tone:
“For the very first time, we are building technology that could become more intelligent than us and that we don’t understand.”
That statement should concern every CX leader deploying generative AI in support, marketing, analytics, or personalization.
If your customers sense unpredictability, bias, or opacity, they disengage.
And disengagement is the most expensive failure in customer experience.
Why Did AI Safety Connect Matter Strategically?
It marked the first major global AI safety convening in the Global South, signaling a shift toward inclusive governance.
This wasn’t another Silicon Valley conversation.
India’s scale, linguistic diversity, and digital public infrastructure positioned it as a central actor in shaping AI’s global trajectory.
Former India G20 Sherpa Amitabh Kant emphasized equitable deployment:
“If AI is not utilised by vast segments of populations… then AI is not fit for purpose.”
For CX leaders, that translates into a core truth:
If your AI excludes segments of customers, it fails strategically.
Inclusion is not branding.
It is market expansion.
What Are the Real Risks for CX Teams?
The risk is not just model failure. It is trust fragmentation across journeys, teams, and markets.
The convening highlighted five themes. Three are directly relevant to CX/EX leaders:
- Acceleration Gap – AI capabilities outpace governance.
- Transnational Risk – AI harms cross borders instantly.
- Fragmentation Threat – Different regulatory regimes create inconsistent customer experiences.
Dr. Eileen Donahoe, Founder of Sympatico Ventures, reframed safety:
“Broad societal adoption… won’t happen if governments, enterprises, consumers, and citizens don’t trust in the basic reliability and safety.”
Trust is no longer a soft metric.
It is a prerequisite for AI adoption.
A Strategic Framework for CX Leaders: The TRUST Stack™
To move from theory to execution, CX leaders need operational structure.
Here is a five-layer model inspired by themes from AI Safety Connect.
1. T — Transparency by Design
Make AI explainable at every touchpoint.
Customers must understand:
- When AI is being used
- What data informs outputs
- How decisions are made
Action:
Embed AI disclosure language into journey maps.
Update scripts and digital interfaces proactively.
2. R — Risk-Based Governance
Adopt proportionate evaluation methods aligned to use-case risk.
Lucilla Sioli of the European AI Office noted voluntary codes and risk-targeted evaluations are emerging standards.
CX implication:
- A chatbot for FAQs ≠ AI for credit approval.
- Governance intensity must match impact.
Create a risk-tier matrix:
| AI Use Case | Customer Impact | Required Oversight |
|---|---|---|
| FAQ Bot | Low | Periodic QA review |
| Personalization Engine | Medium | Bias testing quarterly |
| Decision Automation | High | Human-in-loop + audit logs |
3. U — Unified Cross-Functional Oversight
Break silos between CX, legal, IT, compliance, and data science.
Journey fragmentation often stems from internal fragmentation.
Establish:
- AI Governance Council
- Shared KPIs for trust and adoption
- Cross-team AI playbooks
4. S — Safety Metrics That Matter
Dr. Andrew Forrest of Minderoo Foundation warned:
“You can’t manage what you can’t measure.”
Translate safety into measurable CX metrics:
- AI Escalation Rate
- Customer Trust Index
- Bias Incident Frequency
- Model Drift Detection Time
- Employee AI Confidence Score
What gets measured gets resourced.
5. T — Transnational Alignment
Netherlands Prime Minister Dick Schoof highlighted the role of middle powers in shaping governance.
For global CX teams, this means:
- Map regulatory environments by region.
- Align AI standards across markets.
- Avoid “dual experience” trust gaps.
Consistency builds brand equity.
Fragmentation destroys it.
How Does AI Safety Affect Employee Experience (EX)?
Employees are your first AI customers. If they distrust it, external adoption fails.
During a fireside chat, Turing Award laureate Yoshua Bengio warned AI systems may soon perform most cognitive tasks.
That shifts employee psychology.
EX risks include:
- Skill displacement anxiety
- Shadow AI usage
- Reduced accountability clarity
Mitigation playbook:
- Transparent AI role definitions
- Clear augmentation messaging
- AI upskilling programs
- Internal ethics reporting channels
Safety is cultural before technical.
Case Pattern: When AI Outpaces Governance
Across industries, CXQuest has observed a repeating failure loop:
- Innovation sprint
- Rapid deployment
- Customer confusion
- PR backlash
- Governance retrofitting
AI Safety Connect signals a shift toward governance-first design.
The companies represented—Microsoft, Google DeepMind, AWS, and the Frontier Model Forum—are now integrating safety frameworks earlier in development cycles.
CX leaders must do the same.
Common Pitfalls for CX Teams
1. Treating AI safety as compliance only
Safety is a growth enabler, not a constraint.
2. Over-relying on vendors
Third-party AI still impacts your brand trust.
3. Ignoring edge cases
Rare failures become viral crises.
4. Lack of executive ownership
AI governance without a C-level sponsor fails.
Key Insights from New Delhi
- Trust is infrastructure.
- Inclusion defines scale.
- Middle powers shape global norms.
- Safety accelerates adoption.
- Measurement converts intent into action.
The message from AI Safety Connect was clear:
The future of AI is not about speed alone.
It is about coordination.
FAQ: AI Safety and CX Strategy
How does AI safety directly impact customer loyalty?
Unsafe AI erodes trust. Trust erosion reduces repeat engagement and lifetime value.
Do mid-sized companies need formal AI governance?
Yes. Risk scales with exposure, not size. Governance can be lightweight but must be structured.
How can CX teams measure AI trust?
Track disclosure clarity, escalation rates, sentiment analysis, and trust-index surveys.
What role do middle powers play in AI governance?
They shape standards collectively. Global brands must align with these emerging norms.
Should CX leaders attend AI safety events?
Absolutely. These forums shape regulatory and trust expectations that impact customer strategy.
Actionable Takeaways for CX Leaders
- Map every AI touchpoint across the customer journey.
- Classify each use case by risk level.
- Create a cross-functional AI governance council.
- Define 5 measurable AI trust KPIs this quarter.
- Train frontline teams on AI transparency scripts.
- Align regional compliance standards globally.
- Run quarterly bias and drift audits.
- Communicate AI safety commitments publicly.
Tightened Version for Google Discover / PAA Dominance
AI Safety Connect in New Delhi brought 250 global leaders together to coordinate AI safety standards. For CX leaders, the message was urgent: AI trust determines adoption.
As AI systems accelerate toward AGI-level capabilities, governance gaps widen. Speakers emphasized inclusion, transnational cooperation, and measurable safety standards.
For customer experience teams, AI safety is no longer optional. It shapes trust, loyalty, and brand resilience.
Implement risk-tier frameworks. Break internal silos. Measure safety metrics. Align globally.
Because the future of AI will not be decided by capability alone.
It will be decided by trust.
