Insight Snapshot

Outcomes range from freeing 100+ FTEs through automation to accelerating marketing content creation. The key, Taw argued, is starting from outcomes and working backward to metrics that matter.

Hämäläinen reframed the automation narrative, warning leaders not to fixate solely on efficiency. True value, he said, comes from four levers: efficiency, product and service competitiveness, talent renewal, and capital reallocation to growth. Automation creates room to invest, but long-term health depends on reinvention, not just cost-cutting.

Both leaders stressed that AI investment decisions should balance revenue growth, scale efficiencies, customer experience, and firm health (including infrastructure and security). Early adoption may require “leap of faith” funding, but maturity demands sharper KPIs tied directly to customer and operational outcomes.

Industry adoption is accelerating across the board. Life sciences is at the forefront, reimagining drug discovery, clinical trials, and regulatory approval. Yet Hämäläinen noted that what truly sets this AI wave apart is universality: executives themselves are now daily users of AI tools, creating urgency to scale use cases across industries simultaneously.

The session closed with two telling reflections. Taw: “If AI could remove one task, it would be meetings.” Hämäläinen: “Today, AI is prelude. Tomorrow, it’s symphony.” For executives, the message was clear: the score is being written now—measuring value is the leadership imperative.

Moderator

Jayesh Sanghrajka, EVP & Group CFO, Infosys

Speakers

Steve Taw, Principal Operating Officer & SVP, Information Technology Group, Capital Group

Lari Hämäläinen, Senior Partner, McKinsey & Company

But the current wave is different: generative AI has created what Waghray calls “the moment for every human to become AI literate.” Through “level up” training and hackathons, more than 6,000 employees have been equipped to design and test AI solutions.

This grassroots approach has produced bold use cases. Most striking: a nuclear operations specialist AI built with NVIDIA, capable of ingesting five million documents to support PG&E’s Diablo Canyon nuclear plant. It accelerates onboarding, simplifies technical decision-making, and boosts productivity by up to 60%, while keeping humans in the loop for safety.

Other applications include “Peggy,” PG&E’s customer-facing AI bot, which has delivered 25–30% improvements in customer management costs, and AI-enabled digital twins of energy assets to enhance resilience. These initiatives align with Waghray’s tripod model for scaling AI:

• Foundation – secure, responsible infrastructure.
• Democratization – widespread employee engagement.
• Execution – focus on a few high-value use cases with enterprise-wide impact.

The hardest part, he noted, is getting started—laying a “good enough” foundation and moving quickly to execution, rather than chasing perfection. But execution also creates a new challenge: moving from efficiency gains to efficiency capture. To do this, Waghray is building a “trifecta” of accountability, aligning finance, business, and IT leaders on measurable value delivered.

His message was clear: AI literacy and disciplined execution, not endless pilots, will define which enterprises turn potential into performance.

Moderator

Nayeema Raza, Journalist & Filmmaker

Speaker

Ajay Waghray, EVP & CIO, PG&E Corporation

Five years ago, Citizens launched its cloud migration, modernizing infrastructure and simplifying access. That investment has paid off by enabling a data marketplace—a curated platform where thousands of employees now access trusted data, up from just hundreds a year ago. Adoption has surged 20x in six quarters, proving that people embrace tools when foundations are solid and well-communicated.

Citizens applies this framework through three priorities:

• Focus on value—every project must tie to customer or business impact.
• Build strong foundations—cloud, modern data, and simplified architecture.
• Enable people—through education, marketing, and recognition programs that drive adoption.

Swamy likens this to Formula One: you need both a great car (technology) and a great driver (talent). Without both, the race is lost.

Use cases illustrate this approach. The data marketplace democratizes access, while advanced profitability analytics now integrate customer, household, and corporate relationships—replacing fragmented Excel models with a single source of truth. Leaders can finally see customer P&L across the enterprise, improving service and profitability.

Swamy cautioned against over-fixation on AI’s novelty. The true differentiator is how organizations change expectations, habits, and accountability. Citizens uses carrots and sticks: public recognition of “power users” and top learners, paired with governance that discourages fragmented, duplicative work.

His message to executives: AI will be everywhere. Competitive advantage comes from how you prepare people, simplify foundations, and relentlessly link projects to value.

Moderator

Nayeema Raza, Journalist & Filmmaker

Speaker

Krish Swamy, Chief Data and Analytics Officer, Citizens Financial Group, Inc.

Mitra noted the scale of the challenge: 7,000 identity attacks per second, nearly double last year’s rate. At the same time, Microsoft’s research shows 82% of organizations plan to deploy AI agents within 12–18 months to stay competitive. The paradox is clear: productivity demands unprecedented data access, yet that very access multiplies risk.

Microsoft’s strategy, anchored in Purview for AI, tackles this tension directly. By embedding controls around identity, data access, and monitoring, Purview helps enterprises unlock AI’s potential without losing trust. The bumper-sticker version, Mitra quipped: “Humans and AI move data. Protect that.”

Partnership is also essential. Mitra highlighted Microsoft’s collaboration with Infosys to help enterprises navigate AI adoption without paralysis. Success requires ecosystem-wide alignment, not siloed efforts.

The cultural dimension matters just as much as the technical. Drawing on Satya Nadella’s philosophy, Mitra emphasized three attributes of AI-first organizations:

• Growth mindset—approaching AI as tomorrow’s technology, not retrofitted onto yesterday’s processes.
• Augmentation, not replacement—cAI should elevate human capability, creating “superhumans.”
• Shared learning journey—no company has all the answers; leaders must lean in collectively to evolve best practices.

For executives, the message was blunt: don’t bolt on security later. Build it in now. Those who wait risk stalled deployments and eroded trust. Those who act can transform AI from hype to competitive advantage—by making security and trust the ultimate differentiators in an AI-first world.

Moderator

Mariana Atencio, Peabody Award-Winning Journalist & Bestselling Author

Speaker

Rudra Mitra, Corporate VP, Purview for AI, Microsoft

Bhaumik stressed that being AI-first requires balancing grassroots innovation with disciplined governance. At Nutrien, any employee can propose an AI idea, but it must be sponsored by a senior leader and reviewed by an AI council spanning legal, IT, and business leadership. This ensures experimentation is tied to business value, not “shiny objects.”

The company rejects endless pilots. Instead, each idea is given six weeks to prove viability. Projects either fail fast or build a full business case for scaling. This discipline has moved dozens of use cases into production—more than many peers—while maintaining strategic alignment and financial rigor.

Nutrien frames AI opportunities in three buckets:

• Everyday AI – tools like copilots that will soon be as ubiquitous as email.
• Continuous improvement – enhancing existing processes, such as safer, surface-level potash mining.
• Game changers – bold bets to transform grower experiences, powered by Nutrien’s unmatched network of agronomists and customer trust.

For Bhaumik, the secret sauce is not technology but people, adaptability, and purpose. Drawing from personal experience of food insecurity, he underscored the importance of humility and resilience. Technology is widely available; what differentiates leaders is vision, discipline, and the ability to mobilize people around bold goals.

His message to executives was clear: AI-first organizations aren’t built on tools alone. They emerge when purpose, governance, and people align to turn technology into tangible value.

Moderator

Mariana Atencio, Peabody Award-Winning Journalist & Bestselling Author

Speaker

Debasis “DB” Bhaumik, VP of Information Technology, Nutrien

Navratilova credited early support from family and coaches with shaping her drive, but stressed that persistence and self-belief mattered more than talent. Her aggressive, net-charging style was a calculated risk—one that went against orthodoxy but ultimately defined her dominance. “Calculated risk,” she noted, “is what separates winners from followers.”

Her long rivalry with Chris Evert illustrated another principle: competition sharpens excellence, but respect sustains it. Though fierce on court, they remained collaborators and friends, demonstrating that healthy competition can raise performance without eroding trust.

Adaptability was another recurring theme. Navratilova reinvented her game at 32, overhauling technique to match advances in equipment and athleticism. “You have to evolve,” she said. “I was never afraid to try new things, because I could always go back to the old way.” For today’s leaders, the parallel is clear: embrace change before necessity forces it.

Beyond sport, Navratilova has been a pioneering LGBTQ+ advocate since 1981, urging executives to use their platforms for positive change. Her advice: “Don’t listen to your head or your heart—listen to your gut. And don’t be afraid to ask for help—or to be the one others can ask.”

Asked what it takes to be a champion, Navratilova was blunt: perseverance, self-honesty, and kindness to oneself. Winning, she argued, is less about outcomes than about consistently showing up with effort, integrity, and the willingness to adapt.

For business leaders, her message resonates: boldness, reinvention, and authenticity aren’t just traits of champions—they’re prerequisites for enduring success.

Speakers

Martina Navratilova, 18-time Singles Grand Slam Champion & Tennis Legend

Eva Saha, Master of Ceremonies

Use cases aren’t side projects; they are the budget engine that justifies platform upgrades (Snowflake, Foundry), process mining (Signavio), and responsible-AI guardrails spanning legal, HR, PR, and ops.

Endless pilots are out. PG&E moves from idea to production when a use case proves tangible value—risk reduction, outage minutes saved, customer trust gained. That discipline now underpins millions of automated customer interactions (via PolyAI and guided knowledge), 30–40% faster agent ramp-ups, and “smart ETOR” models that predict restoration by unifying smart-meter, asset, sensor, and customer data.

PG&E frames AI value across three buckets:

• Grid Safety & Reliability – Enhanced power-line safety settings, sectionalization devices, and pole-mounted sensors (e.g., GridScope) catch anomalies earlier and shrink outage blast radius.
• Customer Operations at Scale – GenAI accelerates training, resolves 4–5M calls, and personalizes restoration updates anchored in unified data.
• Planning & Decarbonization – A San Jose digital twin layers GIS, LIDAR, ADMS/SCADA, and undergrounding to fast-track design, permitting, and net-zero scenarios—Dash calls it a “sandbox with a brain.”

Speed doesn’t sacrifice resilience. Every AI use case passes a governance funnel; technology debt is retired (e.g., S/4HANA), so innovation isn’t built on cracks. Planning horizons have shortened to quarters, but the audacious north star endures: “Catastrophic wildfires shall stop.”

The takeaway for leaders: AI-first utilities aren’t tool-first. They’re purpose-first—aligning mission, governance, platforms, and people to convert intelligence into safer grids, faster restoration, and measurable public good.

Moderator

Nayeema Raza, Journalist & Filmmaker

Speakers

Ajay Waghray, EVP & CIO, PG&E Corporation

Ashiss Kumar Dash, EVP & Global Head, SURE, Infosys

Swamy’s “surprises” cut both ways. Negatively, even elite business leaders often lack AI/LLM basics—so literacy is step one. Positively, broad access to training unleashes hidden talent; a bank teller’s thank-you note for a self-serve data program became his favorite proof that people scale impact when given the chance. Citizens now prioritizes operational metrics (NPS, first-call resolution, year-one attrition) first—trusting financial gains to follow—while reminding teams that prompts, time, and shared best practices are as critical as models.

Taw frames AI as a top-10 strategic investment—funding enterprise enablement and a handful of transformative bets—while letting business units pilot, prove, and expand targeted wins (e.g., SDLC acceleration). The goal isn’t only efficiency; it’s doing more, faster. Watch the creeping cost of “GenAI add-ons” in SaaS, he cautions, and modernize wisely.

Both leaders stress pragmatism: traditional ML still delivers immediate ROI (fraud models, credit, marketing) but must ship in months, not years—demanding standard tools, better data, and risk partners who validate at speed. On agentic payments and AI-driven decisions, expect low-value, low-risk starts and gradual scaling; in money movement and investing, reliability and human conviction remain non-negotiable.

The execution blueprint

• Educate first: Lift AI literacy across business roles; share prompt patterns and time to practice.
• Value beyond cost: Anchor to CX and ops metrics; let P&L follow durable improvements.
• Dual-track funding: Enterprise-level “big bets” + BU pilots that graduate on evidence.
• Ship ML now: Standardize data/tooling and compress model cycles (12 months → 4).
• Human-in-the-loop: Keep reliability and judgment central for payments and investing.
• Security as a team sport: Infosec, data, risk, and engineering must co-evolve policies dynamically.

Bottom line: treat AI as habit, not hype—go small where risk demands, go fast where proof exists, and let people be the force multiplier.

Moderator

Dennis Gada, EVP & Global Head, Banking & FS, Infosys

Speakers

Krish Swamy, Chief Data and Analytics Officer, Citizens Financial Group, Inc.

Steve Taw, Principal Operating Officer & SVP, Information Technology Group, Capital Group

DB framed Nutrien’s operating model around three lanes:

• Everyday AI (copilots that lift knowledge work and personal productivity)
• Targeted AI (continuous-improvement systems like vision models predicting underground conveyor failures)
• Game-changing AI (reimagining agronomy itself to grow farmer mindshare and revenue).

ROI follows accordingly: targeted AI often “pays for itself,” everyday AI becomes table stakes for talent and resilience, and game-changers deserve bold investment because disruption is inevitable.

On risk and competition, DB spotlighted two Nutrien moats—and where they could be attacked: the agronomist–grower relationship (deep trust that steers purchases) and a hyperlocal, time-critical supply chain. Both are defendable, but AI-native entrants can erode relationship and logistics edges if incumbents move slowly.

The hardest work is change management. Nutrien invested in “level-up” programs (DataQ, promptology) for broad literacy, top-down deep dives for leaders, and a cross-functional AI Council—more an engagement platform than a policing body—to share ownership of outcomes. DB stressed reframing from deterministic expectations to probabilistic reality: let AI generate plans, trends, and starting points; keep human judgment on safety-critical and financial close decisions.

On culture and pace, Nutrien prizes an action bias (“no POCs”) and accepts learning debt: moving fast once led the team to build chat capabilities that later overlapped with vendor tools; elsewhere, a modeling effort failed until sensor calibration caught up—humbling reminders that timing and foundations matter.

Key Takeaways

• No pilots—ship value: Treat speed as strategy; iterate in production.
• Three-lane model: Everyday, targeted CI, and game-changing AI.
• Defend the moats: Agronomist trust and local, time-critical supply.
• Probabilistic mindset: AI proposes; humans decide where stakes are high.
• Change is a team sport: Literacy programs + AI Council for shared accountability.

Moderator

Mariana Atencio, Peabody Award-Winning Journalist & Bestselling Author

Speakers

Debasis “DB” Bhaumik, VP of Information Technology, Nutrien

Kapil Nanchalal, VP, SURE, Infosys

Without strong identity, data classification, and attack prevention, AI expands risk faster than value. With them, it compounds productivity safely.

Microsoft rejects “bolt-on later” security. Instead, security shifts left into the developer toolchain (e.g., Copilot Studio) and ops surface (observability of what agents accessed, under which credentials, and why). Purview becomes the nerve center: classifying and protecting sensitive data, enforcing DLP, capturing prompts/responses for legal and audit, and governing access as agents talk to agents. Defender addresses AI-specific threats (prompt injection, model tampering), while Entra formalizes agent identities and policies. Sentinel and an AI-assisted SOC complete the loop so human analysts can scale with machine speed.

Infosys’ role is twofold: co-build and land. Internally, Infosys applies Responsible AI (12-domain toolkit), embeds Purview via SDKs, and operationalizes governance. With clients, it moves from proofs to production—e.g., large Purview rollouts (25k+ users) with auto-classification, inline DLP, and Sentinel integration—turning blueprints into measurable outcomes.

Microsoft frames AI security across four execution pillars:

• Identity (Entra): Agents get first-class identities, least-privilege, and policy-as-code.
• Data (Purview): Classify, protect, and log every AI interaction; make governance developer-friendly.
• Defense (Defender): Detect and block AI-native threats (prompt injection, data exfil, model abuse).
• Operations (Sentinel): AI-assisted SOC for scale, speed, and end-to-end observability.

Message to leaders: AI will join the workforce at unprecedented scale. Trust won’t come from tools in isolation, but from identity-first design, data-centric governance, and disciplined, developer-embedded security that turns intelligence into resilient value.

Moderator

Mayank Agarwal, VP, Cybersecurity, Infosys

Speaker

Rudra Mitra, Corporate VP, Purview for AI, Microsoft

Beyond adopting large language models, the company is also developing smaller, specialized models tailored to client needs. What distinguishes leaders, Parekh stressed, is readiness: firms with strong data infrastructure and cloud foundations move fastest in scaling AI. Cloud and data remain the bedrock of digital transformation. While most clients are in multi-cloud environments, success lies in preparing infrastructure for AI-driven workloads. Data maturity—modernizing legacy systems, managing structured and unstructured sources—has become the accelerator for AI adoption.

Infosys also highlighted its delivery-first DNA. Parekh shared a candid anecdote: a U.S. client CEO spent 20 minutes explaining why they replaced another vendor before praising Infosys’s project team. For Parekh, this underlines the company’s edge: not flashy marketing, but dependable execution at scale.

Key priorities include:

• Cost discipline: automation, lean practices, and AI-enabled productivity.
• Strategic platforms: deep expertise in SAP S/4HANA rollouts across regions.
• Partnerships & acquisitions: targeted deals in consulting and niche innovation, supported by an active partner ecosystem.
• Community impact: initiatives like Springboard, which has provided digital education to over 10 million people worldwide.

Parekh closed with the ethos of “One Infosys”—integrating capabilities across the firm to bring the full force of its expertise to every client engagement. In his words, innovation is vital, but delivery is the true differentiator.

Speaker

Salil Parekh, CEO & MD, Infosys

The starting point was daunting: an enormous library of manuals, safety systems, and product data that made responding to customer inquiries slow and inconsistent. Kia’s answer was to build a “24/7 Kia Librarian”—a GenAI system with a photographic memory of every manual, able to deliver precise answers in seconds. The impact has been measurable: a 5% increase in customer contacts handled, while reducing staffing needs by 12%.

Beyond search and support, Kia tackled inefficiencies in surprising places—including physical mail. By automating how scanned letters are read, classified, and routed, the company freed resources from manual drudgery and redirected them to higher-value work.

Crucially, Cameron underscored the human dimension of AI adoption. The first reaction from staff was fear—“Will my job go away?” Kia’s leadership responded by reframing AI as “augmented intelligence”, not artificial. By focusing on pain points that employees themselves identified—and positioning AI as a tool to make their jobs easier—the company built trust and enthusiasm.

Looking ahead, Kia is exploring agentic AI for content generation and automated customer responses, but with a cautious, internal-first rollout to ensure stability before customer-facing deployment. For Cameron, the next unlock is agility: the ability to pivot quickly as new regulatory and customer needs emerge.

The takeaway for leaders: efficiency gains are real, but the real differentiator is how you bring your people along. As Cameron put it, “AI’s value is making it easier for everyone to do the right thing.”

Moderator

Nayeema Raza, Journalist & Filmmaker

Speaker

Michele Cameron, Executive Director & Chief Customer Officer, Kia America, Inc.

Ameritas, a 150-year-old diversified insurer, created the Chief AI Officer role to signal that AI is not just a tool but a strategic transformation lever. Wiedenbeck described a progression familiar to many firms: AI helps people do work, then AI does the work, and eventually, enterprises must rethink how work gets done altogether.

A striking example came from dental insurance claims. Six years ago, Ameritas deployed AI to read X-rays. Accuracy began at 60%, but rather than waiting for perfection, they kept it running alongside human review. Today, the system covers 28 dental procedures at 99.9% accuracy, with dentists now validating rather than redoing results. The lesson: adoption drives improvement, not endless piloting.

In back-office functions, Ameritas has shifted tasks like beneficiary or address changes to AI “assistants” (affectionately named Herbie). This reframes human roles from task execution to oversight and enablement. The payoff: measurable cost savings, higher quality scores, and scalable efficiency gains.

Wiedenbeck urged leaders to resist the instinct to pilot endlessly. “Don’t wait for perfect—implement, learn, and evolve.” AI, he argued, is the dumbest it will ever be today. It only improves with use and context. The risk of inaction is greater than the risk of imperfection.

For executives wrestling with AI strategy, Ameritas offers a bold takeaway: treat AI not as an add-on, but as the engine of a new era of enterprise reengineering—where human-AI synergy redefines efficiency, scale, and value.

Moderator

Nayeema Raza, Journalist & Filmmaker

Speaker

Richard Wiedenbeck, SVP & Chief AI Officer, Ameritas

By 2045, California expects 90% of vehicles and buildings to be electrified, driving an 80% increase in power demand and requiring a sevenfold increase in infrastructure investment. For SCE, meeting that challenge is impossible without AI. Inlander described how SCE is weaving AI into operations—not just generative AI, but also computer vision for equipment inspections and fault detection. Wildfires have made the stakes urgent: grid reliability and safety for 15 million Californians depend on accelerating adoption. “We cannot meet demand the normal way—by adding more people,” he stressed. AI is the only path to autonomy on the grid, resilience at scale, and cost-effective delivery.

Yet technology alone isn’t enough. Transformation in a 140-year-old, highly regulated utility requires cultural change. Employees fear job loss, and Inlander confronted this head-on: AI won’t take your job, but people who know AI will. The strategy is upskilling and reskilling, equipping teams with digital tools to ensure relevance in a fast-changing environment.

Surprises have come along the way. Wildfires underscored the urgency to move faster, while employee adoption of tools like Copilot has been slower than expected. The lesson: leadership must sponsor bold initiatives, accept failures, and encourage teams to experiment without fear.

SCE knows it cannot transform alone. Partnerships with Infosys, AWS, SAP, and other technology providers are critical to modernizing infrastructure and embedding AI into daily operations. For Inlander, the message is clear: in one of the world’s most progressive energy markets, the grid of the future will be built not just with steel and wires, but with intelligence, resilience, and trust.

Moderator

Mariana Atencio, Peabody Award-Winning Journalist & Bestselling Author

Speaker

Todd L. Inlander, SVP & CIO, Southern California Edison (SCE)

Infosys research shows only 48% of marketing AI initiatives deliver impact, while MIT finds over 90% struggle to extract value. The problem: treating AI as a side experiment rather than embedding it in core business processes.

Hahn argued that AI must move beyond proofs of concept and into scaled execution. Pilots have a role—but only if they lead to enterprise-wide rollout. Otherwise, organizations risk chasing novelty without capturing measurable value. Virmani agreed, cautioning that early AI was oversold as instant productivity. True impact, he stressed, comes when AI spans the full job-to-be-done lifecycle—from efficiency to customer experience to effectiveness.

Both leaders emphasized that data integration is now the critical differentiator. Without enterprise data stitched together across silos, personalization at scale remains an illusion. Hahn described the risk bluntly: companies that fail to unify data will face competitive disadvantage.

The human dimension also looms large. Employees worry that AI will erase jobs. Leaders must reframe AI as augmented intelligence—a tool to remove pain points and free people for higher-value work. Open communication, transparency, and embedding IT talent directly in marketing teams can help bridge trust and unlock innovation.

Virmani summed it up with an example: Infosys’s AI-powered personalized annual report, where every shareholder could appear on the cover. AI makes “magic at scale” possible—but only when CMOs and CIOs build together.

Moderator

Nayeema Raza, Journalist & Filmmaker

Speakers

Laura Hahn, Unit CIO & VP IT, Johnson Controls

Sumit Virmani, EVP & CMO, Infosys

A central theme was the fusion of technology and culture. On the technology side, automation and AI-powered solutions were highlighted as catalysts for exponential gains, enabling processes to run faster and with fewer errors. However, Kia cautioned that technology alone cannot deliver transformation. Without cultural adoption — where employees trust, embrace, and actively leverage new tools — the efficiency gains are limited.

The AMA format allowed for a practical exploration of real-world challenges:

• Overcoming skepticism from employees concerned about job displacement.
• Ensuring that leaders communicate the “why” behind efficiency initiatives.
• Balancing speed with accuracy when automating critical workflows.

Kia also pointed to prioritization as a guiding principle. Instead of dispersing resources, Ameritas focused on identifying the most impactful bottlenecks and addressing them in ways that delivered benefits across multiple departments. This approach created ripple effects, magnifying results beyond the immediate process improved.

Finally, the conversation reinforced a customer-first mindset. Exponential efficiency is not simply an internal metric; it is measured by how effectively and reliably the organization delivers value to clients.

Key Takeaways

• Efficiency is a growth enabler, not just cost reduction.
• Tech + culture fusion is essential — adoption drives outcomes.
• Communicate the “why” to overcome resistance and fears.
• Focus on high-impact bottlenecks for maximum ripple effect.
• True efficiency must be customer-centered in outcomes.

Moderator

Nayeema Raza, Journalist & Filmmaker

Speakers

Michele Cameron, Executive Director & Chief Customer Officer, Kia America, Inc.

Rakesh Gollapalli, SVP, Automotive, Aerospace, & Defense, Infosys

Subba Kethu, Digital Transformation Leader and the Head of IT, Kia America, Inc.

A key theme was the integration of AI and intelligent automation across workflows. Instead of siloed tools, Ameritas built interconnected processes that allow data and tasks to flow seamlessly between departments. This reduced redundancies, sped up decision-making, and improved accuracy in routine operations.

Another important element discussed was change management. Efficiency gains required not only the right technology but also strong buy-in from leadership and teams. The company invested in training, clear communication, and aligning new tools with employee needs. This cultural adoption ensured that automation was seen as empowering rather than threatening.

The session also highlighted the shift in enterprise mindset: moving away from incremental improvements (e.g., shaving minutes off a process) toward exponential scaling opportunities. By identifying bottlenecks that affected multiple departments and solving them holistically, Ameritas achieved outsized results.

Finally, the discussion stressed customer-centricity — efficiency is not just internal. Faster, more accurate, and scalable processes ultimately translated to better service quality, reduced errors, and enhanced client trust.

Key Takeaways

• Exponential efficiency = scaling intelligently, not simply working harder.
• AI & automation integration across workflows removes silos and boosts accuracy.
• Change management and cultural adoption are as critical as the tech itself.
• Focus on enterprise-wide bottlenecks for outsized impact.
• Efficiency gains should always align with customer experience improvements.

Moderator

Nayeema Raza, Journalist & Filmmaker

Speakers

Richard Wiedenbeck, SVP & Chief AI Officer, Ameritas

Senthil Velumani, VP, Insurance, Infosys

Being “pretty good” doesn’t change industries—or lives. He challenges leaders to ask themselves: when someone asks who’s the best in your field, is your name mentioned? And if not, why not?

Central to his message is the rejection of fallback options. “Plan B sucks,” Gardner says with conviction. If Plan B were any good, it would already be Plan A. Greatness—whether Michael Jordan’s championships or Oprah Winfrey’s media reign —comes from singular focus.

But focus doesn’t mean rigidity. Gardner highlights the importance of “hard pivots”—decisions we would never choose, but must make work. For him, that meant learning to connect with audiences virtually during the pandemic, embracing new tools without abandoning authenticity.

Gardner also reframes success through integrity and resilience. In hiring, he shredded résumés to ask candidates not about achievements, but about failures: What scar tissue do you carry? What did you learn? Scar tissue, he insists, is the true signature of survival.

For leaders navigating today’s volatility, Gardner’s counsel is deceptively simple: trust your gut, guard your integrity, and commit fully. Above all, value time—the one asset you can never regain. His closing words resonate as a call to action: “Now is the new next. Do it now. Say it now. Be it now. Because tomorrow is never guaranteed.”

Speaker

Chris Gardner, International Best-selling Author & Award-winning Film Producer