Product management is the best path to senior leadership

Watch on YouTube

TLDR

In my recent interview with Elizabeth Samara-Rubio, Chief Business Officer at SiMa.ai, we explored the journey from product management to senior leadership. Elizabeth shared how her product management experience at HP and other companies shaped her approach to business leadership. She emphasized the importance of setting a clear North Star for teams, challenging assumptions with data, and creating a culture that embraces calculated risk-taking. Her insights on Edge AI applications revealed how companies are gaining competitive advantages through both product-focused and process-focused AI integration strategies.

Key Topics

• How product management experience provides a foundation for executive leadership
• Setting direction as a senior leader through clear vision and metrics
• Edge AI applications and benefits: privacy, security, and cost advantages
• Creating customer value through innovation and “getting your own truth”
• Building a data-driven leadership culture
• Two approaches to AI integration: product-focused and process-focused
• Advice for product managers aspiring to senior leadership roles

Introduction

When you meet an exceptional product manager – a product master – you’re often seeing a future business leader in the making. They have a spark – an obsession with customer needs, a knack for strategy, an ability to unite teams around a vision – it’s the same DNA that builds great companies. Our guest today embodies this evolution, taking her product management foundation to pioneer AI innovation and lead high-growth companies. 

From launching products at HP in the late 90s to driving AI innovation today, Elizabeth Samara-Rubio’s journey offers unique insights into how product management shapes business leadership. As Chief Business Officer at SiMa.ai, she’s now at the forefront of Edge AI technology, bringing artificial intelligence directly to devices where decisions need to be made. In this discussion, we’ll explore how Elizabeth’s early product management experience influences her approach to building high-growth, customer-focused companies. We’ll also dive into her perspective on AI’s transformative impact on industries, drawn from her work at the intersection of strategy, product, and artificial intelligence. 

Whether you’re a product manager looking to expand your influence or a business leader interested in the impact of AI on your industry, Elizabeth’s insights bridge the gap between product thinking and company building. 

From Product Manager to Business Leader

Product managers are prepared to be leaders, as the challenges of balancing multiple stakeholders, making data-driven decisions, and keeping customers at the center of everything you do are experiences that translate directly to executive roles.

The transition from managing products to leading businesses isn’t automatic, however. It requires developing new skills while leveraging the product mindset that made you successful in the first place. As Elizabeth’s journey shows, product managers who successfully make this leap often maintain their customer focus and data-driven approach while expanding their vision to encompass the entire business.

Throughout our discussion, Elizabeth shared insights on setting direction as a senior leader, applying product management tools to business leadership, and leveraging AI to create competitive advantages. Her experiences provide a roadmap for product managers looking to grow their careers beyond traditional product roles and influence entire organizations.

What makes this journey from product manager to business leader particularly relevant today is how technology – especially AI – is transforming products, services, and entire industries. Leaders with product backgrounds are uniquely positioned to guide this transformation.

Setting Direction as a Senior Leader

One of the differences between product management and executive leadership is the scope of direction-setting. While product managers focus on product vision and roadmaps, senior leaders must establish a North Star for entire organizations.

Elizabeth emphasized that setting direction as a Chief Business Officer involves providing sufficient clarity for each function to understand its role. At SiMa.ai, this direction centered on customers who are both anxious and excited about AI possibilities. By establishing customers as the North Star, Elizabeth ensured every team—from product managers to field application engineers and sales—could align their work toward becoming trusted advisors in this space.

But direction-setting isn’t just about vision. Elizabeth highlighted three essential components:

• North Star orientation – Creating a clear, compelling direction that guides decision-making
• Measurable objectives – Establishing metrics to track progress toward goals
• Cultural foundation – Building a culture that supports execution

Setting the numbers is a big part of direction-setting. As her team closed 2024 and entered 2025, measuring their velocity toward objectives became as important as the objectives themselves. This approach creates an early detection system for course corrections.

The cultural element proved particularly vital in a startup environment. As a veteran of six startups, Elizabeth underscored the importance of fostering good judgment, having a bias for action, and learning by doing.

The combination of clear direction, measurable objectives, and supportive culture creates a framework where teams can execute effectively while staying aligned with organizational priorities. For product managers aspiring to leadership roles, this approach to direction-setting represents an expansion of the product-focused planning they already practice.

As senior leaders set direction, they must balance ambition with realism, ensuring their vision energizes the organization while remaining achievable through disciplined execution. This balance becomes the foundation for sustainable growth and innovation.

Understanding Edge AI: Current Applications and Benefits

SiMa.ai operates at the forefront of Edge AI, which involves deploying artificial intelligence directly on devices rather than in the cloud, creating distinct advantages for certain applications.

Elizabeth explained that Edge AI could take the form of conversational AI in vehicles or voice interfaces for industrial equipment operators. The key distinction is that processing happens on the device itself, at the “edge,” rather than in the cloud.

This local processing creates three primary benefits driving Edge AI adoption:

• Privacy – Data remains on the device, reducing exposure of sensitive information
• Security – Reduced vulnerability to network-based attacks
• Cost – Lower operational expenses without ongoing cloud processing fees

For product innovators, these advantages open new possibilities for creating differentiated experiences. Elizabeth described how Edge AI enables personal assistant functionality without requiring users to share personal data with service providers – a potential game-changer for privacy-conscious consumers.

The applications span both consumer and industrial contexts. In vehicles, Edge AI powers conversational interfaces without connectivity requirements. In manufacturing settings, it enables speech-to-text capabilities that help operators follow instructions while performing complex tasks on production lines.

This technology represents a significant shift from cloud-dependent AI systems that require constant connectivity and raise privacy concerns. By bringing AI processing to the device level, product teams can create more responsive experiences while addressing growing data privacy concerns.

For product managers exploring AI integration, understanding this distinction between cloud and edge deployment models helps inform architecture decisions. The right approach depends on specific use cases, data sensitivity requirements, and cost considerations – all factors that product leaders must weigh when developing AI-enhanced offerings.

Lessons from Product Management Experience

When I asked Elizabeth about the most valuable insights from her product management career that influence her leadership approach today, she identified three key principles.

• You’re never going to be popular
• Challenge assumptions
• When innovating, always look for pockets of possibilities and clock speed.

Product managers can’t satisfy everyone’s wishes, and this reality continues in executive roles where difficult trade-offs remain necessary. Learning to make decisions despite inevitable disagreement prepares product managers for leadership challenges.

Challenge assumptions with data. Effective product managers combat confirmation bias by seeking customer conversations, studying competitors, and developing deep technology understanding. This evidence-based approach becomes even more critical in leadership positions where decisions have broader impact.

To find pockets of possibility, Elizabeth looks for teams that have repeatedly tried to solve a problem without success. These represent fertile ground for innovation because they have both motivation and context.

Every person, company, and market has a clock speed. Moving too quickly without bringing others along leaves you alone. Different individuals, organizations, and markets move at different speeds, and effective leaders must understand and accommodate these variations.

This lesson proved particularly valuable as Elizabeth advanced in her career. While early-career product managers might prioritize speed and decisive action, senior leaders must ensure their teams move forward together. This doesn’t mean slowing innovation, but rather bringing others along through clear communication and shared understanding.

Case Study: Creating Customer Value Through Innovation

Elizabeth described a customer-focused innovation she spearheaded approximately a decade ago. This case study illustrates how product leadership principles translate into tangible business outcomes.

Elizabeth had joined a company experiencing declining growth rates. The CEO wanted to break out of this pattern, but the parent company valued consistency and predictability, creating a challenging innovation context.

Rather than pursuing entirely new products or markets, Elizabeth focused on identifying unmet needs within existing customer relationships. This meant going beyond what customers explicitly requested to uncover deeper problems.

The company sold sophisticated machine vision systems to manufacturing clients – equipment costing between $200,000 and $500,000 per unit that could detect defects as small as black pepper at speeds exceeding 70 miles per hour. When customers began asking for price reductions, the typical response might have been to either refuse or comply.

Instead, Elizabeth took a journalistic approach to customer research, seeking her “own truth” about what was really happening. Through direct observation and conversations, she discovered customers were incurring increasing costs managing these systems. Every morning, teams of four would walk production lines to document system health and operational status – a reactive, time-consuming process.

With this insight, Elizabeth partnered with the CTO to create the company’s first cloud-based asset health monitoring system with an analytics dashboard and proactive alerts based on trending data. They accomplished this in just eight weeks, breaking numerous organizational rules in the process.

Within those eight weeks, over 80 systems were running with the new monitoring service, opening a new revenue stream with existing customers without lowering prices. The innovation solved customer problems while creating business value.

This experience reinforced Elizabeth’s belief in discovering customer truths firsthand. Rather than relying on secondary sources, Elizabeth advises product managers to act like journalists and “go get your own truth.” Product leaders who directly engage with customers often uncover opportunities others miss.

Tools and Frameworks for Product Leadership

Among the product management tools that Elizabeth has carried into leadership, “get your own truth” remains most valuable. As product managers advance into leadership positions, they typically have fewer opportunities for direct customer interaction and hands-on product work. This distance creates risk, making deliberate truth-seeking even more critical.

She described how, as a product manager, she would meticulously document what she wanted to be true for a product to succeed, then deliberately seek evidence to disprove those assumptions. This practice protected against confirmation bias and ensured decisions remained grounded in reality rather than wishful thinking.

In leadership roles, Elizabeth applies this same approach at a broader scale. While leaders must communicate optimistic, motivating narratives about the future, they must simultaneously maintain discipline in checking assumptions during execution. Leaders who fail to verify their assumptions often make costly strategic errors.

This balancing act – between inspirational vision and rigorous validation – represents a key leadership skill that product management experience helps develop. Product managers regularly navigate similar tensions between aspirational roadmaps and practical constraints.

The tools themselves matter less than the mindset behind them. Whether using formal frameworks like the Business Model Canvas or creating customized approaches, effective product leaders maintain intellectual honesty about assumptions and actively seek disconfirming evidence.

For product managers aspiring to leadership positions, this suggests the value of developing robust processes for assumption-testing and truth-seeking that can scale beyond individual product decisions to organizational strategy.

Building a Data-Driven Leadership Culture

Elizabeth’s emphasis on challenging assumptions naturally connected to another key theme in our conversation: creating a culture where data drives decisions. She shared specific approaches for establishing this culture within her organizations.

When Elizabeth joined her current company, she made her expectations immediately clear. She told her team, “I might not remember your names right away, but if you gave me your phone number, I would remember that.” This light-hearted comment conveyed a serious message: Numbers matter. She explained that she expects everyone to know their numbers intimately – not just as figures on a slide but as deeply understood indicators of performance.

This expectation works both ways. Elizabeth models the behavior by knowing her own numbers thoroughly, ensuring she can respond immediately when her CEO asks for metrics.

Beyond setting expectations, Elizabeth creates an environment where team members feel safe sharing negative information. She regularly tells her teams, “I’m going to tell you what I believe, but then you need to tell me what I missed.” This invitation to point out blind spots and challenge assumptions creates psychological safety while reinforcing the value of evidence over opinion.

Elizabeth outlined five key indicators for customer success:

1. Baseline number of users
2. Velocity (how quickly users are being added)
3. Recency (frequency of user acquisition)
4. Duration (user retention)
5. Expansion (increased usage or adoption)

While traditional metrics like customer acquisition cost remain important, they function more as signals about investment efficiency rather than indicators of strategic direction. For internal operations, metrics focus on timeliness, early delivery, and error rates after launch.

Elizabeth’s approach involves tracking 8-9 high-level KPIs annually, each supported by 2-3 subordinate metrics. This creates an early detection system for potential issues, allowing course correction before problems become serious.

By establishing clear expectations around metrics, modeling data-driven decision-making, and creating safety for sharing concerning information, Elizabeth builds a culture where evidence trumps opinion and problems surface early enough to address effectively.

AI’s Impact on Product Innovation and Business Processes

Elizabeth identified two distinct approaches companies are taking in incorporating AI into their products and processes.

On the product side, organizations are using AI for differentiation in increasingly competitive markets. Elizabeth shared an example of a company that ranked third globally in market share for equipment used in EV battery production. Facing price pressure from Asian competitors, they needed to differentiate without sacrificing margin.

Rather than competing solely on price, they partnered with SiMa.ai to embed AI directly into their equipment. This shifted the value proposition from simply inspecting completed products to detecting early warning signs during the manufacturing process. The AI system identifies when processes are trending toward poor outcomes and automatically adjusts calibration to maintain quality.

This approach transformed the offering from reactive quality control to proactive quality assurance. Instead of identifying defects after production, the system prevents them from occurring. For customers, this means higher yields and less waste. For the equipment manufacturer, it creates sustainable differentiation that justifies premium pricing.

On the process side, Elizabeth described another customer in a regulated industry that integrated AI not into products but into their operational workflows. This company implemented AI for quality inspection while meeting strict FDA requirements. The technology enabled a complete process redesign that improved throughput by 20-40%.

This AI implementation catalyzed broader transformation, leading the company to introduce robotics into their operations for the first time. The AI capability became the foundation for reimagining their entire production approach.

Both examples highlighted the three key drivers for Edge AI adoption: reduced latency (faster processing), enhanced privacy (keeping data local), and optimized costs (avoiding ongoing cloud expenses).

For product managers, these cases demonstrate how AI can create value beyond simple feature enhancement. Whether embedded in products or integrated into processes, AI enables fundamental rethinking of how value is delivered to customers. This represents a significant shift from earlier AI implementations that focused primarily on post-production applications.

Advice for Product Managers Aspiring to Senior Leadership

I asked Elizabeth what advice she would offer product managers who aspire to C-suite or other senior leadership positions. Her recommendations combined practical skills development with maintaining the essential qualities that make product managers effective.

First, she encouraged product managers to develop a healthy attitude toward risk-taking. Elizabeth noted that product managers often become overly cautious and methodical, worried about making wrong decisions that could impact the entire company. While thoroughness matters, she advised taking more calculated risks while distinguishing between “one-way door” decisions (difficult to reverse) and “two-way door” decisions (easily changed if needed).

Second, she emphasized the importance of knowing your numbers. Elizabeth categorized product managers into three types: “order takers” who simply implement what others request, “storytellers” who paint beautiful visions but struggle with execution, and balanced product leaders who center their work around customers and measurable outcomes. She strongly advised aspiring leaders to develop this balanced approach.

Third, she recommended that product managers create their own narrative around business impact. “Your product is a business,” she stated, suggesting that even if not formally responsible for P&L, product managers should develop their own profit and loss mindset. This business orientation prepares them for broader leadership responsibilities.

Finally, she urged product managers to stay true to what made them product managers in the first place, which probably includes curiosity. Whether exploring customer problems or experimenting with products, this fundamental quality helps product leaders avoid major mistakes. As responsibilities grow, maintaining connection to customers and products becomes more challenging but even more essential.

Elizabeth also highlighted the importance of effective storytelling for leaders. She noted that 80% of communication is non-verbal, advising aspiring leaders to fully commit to their message delivery: “Put your whole body into it. Get into it. This is your thing.”

Conclusion

For product managers looking to expand their influence and move toward leadership roles, this balance between technological enthusiasm and business purpose provides a valuable compass. The journey from product manager to business leader isn’t about abandoning product thinking but about applying it at increasingly strategic levels. As Elizabeth’s career demonstrates, the skills that make exceptional product managers – customer obsession, strategic vision, and the ability to unite teams – are precisely the qualities that build outstanding business leaders.

Useful Links

• Learn more about SiMA.ai and see what upcoming events they’ll be at
• Connect with Elizabeth on LinkedIn

Innovation Quote

“Science is wonderfully equipped to answer the question ‘How?’ but it gets terribly confused when you ask the question ‘Why?'” – Erwin Chargaff 

Application Questions

1. How could you implement Elizabeth’s “get your own truth” approach in your current role? What specific steps could you take to gather firsthand customer insights beyond what’s provided through sales or marketing channels?
2. How might you balance the “clock speed” of your product innovation with your organization’s ability to absorb change? What signals would tell you that you’re moving too quickly or too slowly?
3. What metrics do you currently track for your product, and how do they compare to Elizabeth’s five key indicators (baseline users, velocity, recency, duration, and expansion)? Which additional metrics might you add to create an early detection system for potential issues?
4. How could you apply the distinction between “one-way door” and “two-way door” decisions to take more calculated risks in your product development process?
5. If you were to create your own P&L mindset for your product today, what would be the key revenue drivers and cost factors you would track? How might this perspective change your current priorities or decision-making approach?

Bio

Elizabeth Samara-Rubio is a 20+ year tech industry veteran where she’s led customer experience programs in industrial and manufacturing sectors in addition to global go-to-market efforts for AI services across many domains. As Chief Business Officer of SiMa.ai, Elizabeth is responsible for ensuring the company is developing products that serve client needs while going above and beyond the industry status quo. 

Elizabeth has held various high-level roles across the software industry, including a tenure at AWS. While at AWS, she was the Global Head of Language, Vision, Industrial, Applied AI+GenAI Use Case GTM & Business Development, leading the global go to market AI specialist team to adopt and scale AI services. She also founded and served as CEO at clean-energy startup, StorWatts. 

Elizabeth holds a BA in Business/Marketing Communications from the University of Illinois and an MBA in Information Management from the Texas McCombs School of Business. 

Thanks!

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

Source