Over the last 20 years, Pranav Shahi has developed a framework-driven approach to technology innovation that delivers measurable business impact. Most recently as Head of Business Technology at ServiceTitan, Shahi played a crucial role in enabling the company’s IPO by driving IT readiness to support Sarbanes-Oxley Act requirements, optimizing the software budget, and ensuring compliance with public market regulations. Previously, at Atlassian, he scaled the IT organization during a period when revenue tripled to $3 billion.
We spoke with Shahi about his systematic approach to pilots, win-win commercial models for technology adoption, and the evolving landscape of AI implementation. His insights reveal how organizations can drive meaningful innovation through disciplined evaluation processes, proactive external engagement, and clear commercial alignment.
This conversation is part of our “Early Adopters” series highlighting business leaders who are driving new initiatives and transformation at major companies. For initiatives to succeed, there must be strong partnerships between Innovation teams and business executives. Through these interviews, we share perspectives from functional leaders who are putting emerging technology into practice.
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How do you engage with the startup ecosystem?
I engage with the startup ecosystem through multiple channels. I provide pro bono advisory support to numerous early-stage technology companies. During my time at Atlassian, I established a quarterly practice of meeting with four companies — typically seed-stage — to provide guidance on use cases, product-market fit, and tech strategy.
I maintain strong connections within the startup community both as an advisor and investor. Currently, my wife and I evaluate approximately four investment opportunities annually. My startup engagement primarily comes through three avenues: venture funds where we’ve made personal investments, portfolio companies connected to my previous employers, and established professional networks.
When evaluating and implementing new technologies, how do you balance quick wins versus long-term transformational change?
I’ve refined a framework over the past 15 years that evaluates impact against effort. I always begin by assessing what business impact we’ll generate and what level of effort is required. Then I conduct a comprehensive fit assessment across three key dimensions. First, I evaluate business fit — determining if the solution addresses specific use cases and resolves genuine business pain points. Second, I assess technical fit to ensure alignment with our existing architecture. Third, I conduct a thorough risk assessment encompassing traditional security and compliance considerations, alongside the financial viability of potential vendors.
Once these evaluations are complete, I advocate for measured implementation. I begin with a pilot, validate success metrics, and then scale methodically. This staged approach allows us to balance immediate gains with long-term strategic objectives.
How do you structure pilots with startups?
I deliberately employ an incremental approach to implementation. Rather than attempting full-scale deployment across the organization, I target one specific use case or functional area initially, then strategically expand to encompass the complete user base.
For example, when implementing a knowledge management solution or chatbot, I would typically begin with the IT department, then methodically incorporate the HR team, followed by operations, before finally scaling across the entire enterprise. This measured expansion enables us to identify and address potential challenges at each stage while demonstrating clear value before broader deployment.
I deliberately employ an incremental approach to implementation. Rather than attempting full-scale deployment across the organization, I target one specific use case or functional area initially, then strategically expand to encompass the complete user base.
How long does it typically take to move from pilot to contract?
The timeline varies significantly depending on the specific use case and technology. In the most accelerated scenarios, I’ve completed the transition from pilot to contract in approximately six to eight weeks. However, a more typical timeframe is three to four months.
This timeframe varies based on solution complexity, implementation scope, and organizational readiness. We prioritize thorough evaluation during the pilot phase to ensure that when we proceed to contract, we have clear metrics of success and a well-defined roadmap for broader deployment.
How do you determine when a pilot is ready for broader deployment?
Much of this determination stems from comprehensive upfront work. I focus on establishing a clear big-picture understanding from the outset — conducting thorough discussions to understand the solution’s current capabilities and future roadmap. These initial assessments allow us to chart a strategic implementation plan that identifies our immediate needs while anticipating potential expansion into additional use cases.
After establishing this foundation, I maintain close alignment through structured executive reviews, which provide a consistent framework for staying informed about roadmap developments and identifying incremental value opportunities. This approach ensures that when we expand beyond the pilot phase, we’re doing so with a clear understanding of how the solution will scale.
What characteristics do your most successful startup partnerships share?
The foundation of successful partnerships begins with demonstrated business and technical feasibility. Ultimately, the solution must address a specific pain point within our organization.
I view these relationships as long-term journeys rather than transactional engagements. To illustrate this approach: I once had a seed-stage startup approach me during my time at Atlassian. While their product showed promise, I identified specific capabilities it lacked that would be essential for our needs. When I later moved to ServiceTitan, they reconnected, having implemented those exact capabilities — which led to an immediate partnership that continues today. I maintain active involvement in their development roadmap, providing strategic input while ensuring our respective business objectives remain aligned.
The most successful partnerships demonstrate commercial viability for both parties. Sometimes startups make excessive customizations just to secure a reference customer, only to find the relationship unsustainable long-term. My approach is to emphasize transparent, win-win commercial discussions from the beginning. The most enduring partnerships create mutual value that evolves as both organizations grow.
What does a commercial “win” look like for an enterprise when engaging with a startup vendor?
For enterprise organizations, the primary commercial win centers on accelerated time-to-market in resolving critical pain points. Startup vendors typically demonstrate greater hunger for success, agility in execution, and freedom from bureaucratic constraints.
What differentiates startup partnerships is the nimbleness, adaptability, and accelerated time-to-market in addressing specific business challenges.
What differentiates startup partnerships is the nimbleness, adaptability, and accelerated time-to-market in addressing specific business challenges. These qualities enable enterprises to implement solutions significantly faster than would be possible through traditional vendor relationships or internal development — creating measurable business value through both operational improvements and competitive advantage.
Can you share an example where a particular solution delivered unexpected value to your organization?
I approach technology evaluation through a structured framework, so I rarely encounter truly ‘unexpected’ value. Our assessments are designed to identify potential benefits comprehensively. However, I can share an example where additional value materialized beyond our initial implementation objectives.
We engaged with a vendor for a specific use case, and as implementation progressed, we observed exceptionally high adoption rates for their solution. Notably, their per-user cost was substantially lower compared to an existing enterprise solution addressing similar needs. This discovery enabled us to rationalize our technology stack by transitioning from the higher-cost incumbent solution to this more cost-effective alternative. The result was significant hard-dollar savings and cost avoidance, particularly valuable as renewal negotiations with the previous vendor were approaching.
How do you structure your approach to innovation? Specifically, how do you balance learning from external developments while fostering internal innovation initiatives?
I employ a dual-focused strategy that addresses both external engagement and internal implementation. For external engagement, I pursue three parallel approaches. First, I maintain active participation in select industry forums. I limit my involvement to three to five key groups to ensure meaningful contribution rather than superficial participation. Second, I establish regular business reviews with strategic vendors, recognizing that significant innovation often emerges from existing partnerships. Third, I organize structured innovation showcase days — the frequency varies by organization — creating dedicated opportunities to evaluate emerging technologies.
These external activities provide a continuous flow of innovative concepts into the organization. To effectively apply these insights to our business challenges, I implement a goal-setting framework. We establish annual innovation objectives for teams but review and refine these quarterly, allowing us to adjust our focus as technologies and business priorities evolve.
During these quarterly reviews, we determine whether specific initiatives warrant experimentation, formal pilots, or full-scale implementation. This combination of systematic external engagement paired with disciplined internal goal-setting and regular reassessment has proven highly effective in translating innovative concepts into practical business value.
Where do you see GenAI’s greatest enterprise impact, and its limitations?
I’ve observed three primary areas where GenAI is delivering significant immediate value at the enterprise level. First, in code generation capabilities — particularly in environments where teams are actively building solutions, the productivity enhancements are substantial. Second, knowledge management applications are showing strong returns, including enterprise search optimization and knowledge base article generation, which enable more effective self-service capabilities.
The third area encompasses operational agents that automate repetitive tasks while enabling self-service for data access, queries, and transactions. These applications are particularly effective when integrated through a unified front-end that orchestrates across custom and vendor-provided agents. This orchestration layer is becoming increasingly critical as organizations develop proprietary agents alongside those acquired through vendor solutions. Having a cohesive automation and orchestration technology for GenAI that sits at the front of these systems helps navigate users efficiently through the organization.
Regarding limitations, cost-effectiveness remains a significant consideration. There are instances where GenAI solutions technically address the need but at a cost structure that’s difficult to justify. For example, many vendors are adding AI capabilities with premium pricing of $5-10 per user per month. As these costs multiply across an enterprise, budget constraints force selective implementation —typically limiting organizations to two to four strategic GenAI investments rather than deploying capabilities across all solutions.
Beyond GenAI, which emerging technologies are you watching closely?
I’m particularly focused on the convergence of automation workflows with artificial intelligence. The strategic opportunity lies in embedding AI capabilities directly into transactional workflows — for example, integrating predictive analytics into performance review processes where managers receive AI-generated insights about employee retention risk factors and potential disruption costs.
Spatial computing — including augmented and virtual reality applications — presents significant opportunities for field operations and employee training initiatives. I expect substantial advancements in these areas as the technology matures.
Data management remains a critical focus area. Despite two decades of discussion around data quality, organizations continue to struggle with implementation. Quality governance and self-service data capabilities will be essential priorities.
Finally, I’m monitoring blockchain technology developments, particularly for identity convergence and smart contract applications. I see particular potential in procurement processes, where blockchain could transform vendor security and compliance assessments —creating efficiencies through shared trust mechanisms in vendor evaluation.
Paulina Karpis leads Early-Stage Platform for B Capital, a global multistage venture firm investing in B2B startups.
Featured image by Steven Weeks on Unsplash
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