At The American Bazaar’s “Leadership @ Inflection Points” conference in Vienna, VA, former IRS deputy CIO Darnita Trower and Vyntelliigence chief data officer Mayank Sharma explored how truth, purpose, and trust must anchor the next phase of digital and organizational transformation.
The setting: When leadership meets data
The November 14 panel at *Leadership @ Inflection Points*—moderated by event curator Rohit Tripathi—brought together two professionals who have navigated the data revolution from strikingly different vantage points.
Darnita Trower, now customer experience officer at 22nd Century Technologies, spent a decade at the IRS and served as acting deputy CIO of operations during one of the most turbulent transition periods in federal governance.
Mayank Sharma, chief data officer at Vyntelliigence and a former IBM researcher, has spent more than three decades translating mathematical theory into real-world data systems.
Their dialogue—at once philosophical and pragmatic—grappled with questions that resonate far beyond the federal bureaucracy or Silicon Valley labs:
What is the purpose of data? Who guards its truth? And how should organizations respond when the mechanisms designed to enable progress start dictating it?
From the IRS to the Inflection Point
Trower began by recounting her final months at the IRS—September 2024 through early 2025—when the winds of political transition collided with the realities of tax season.
“It was an interesting time to be in a senior role at the IRS,” she recalled with understatement.
Her team had spent months designing an operational plan that would carry the agency into 2025—only to face a new administration’s transition team “showing up very early,” asking for access, and upending established processes.
The experience, she said, crystallized what an *inflection point* feels like in real time: “You realize that the rules you’ve been following no longer work, and you’ve got to change something.”
Keeping staff focused amid chaos became her principal task. “In those moments,” she reflected, “people look to leaders to see how they should behave. You have to project clarity and mission, even when everything around you feels uncertain.”
The Evolution of Data at the IRS
For Trower, the IRS’s relationship with data has always been paradoxical: “It’s the agency’s biggest asset—and its biggest vulnerability.”
During the COVID-19 era, the agency’s reliance on paper returns exposed its digital shortcomings. “There were literally trailer trucks of paper coming in,” she said.
Her assignment to lead digital transformation—“perhaps because my initials are D.C.”—turned into a turning point for the institution.
Scanning those paper returns, she realized, was only the beginning. “The real question was how to transform scanned images into usable data that drives the taxpayer experience.”
That insight led to innovations like secure digital response tools that allowed taxpayers to communicate electronically. “It was a game changer,” she said. “Our customers—meaning taxpayers—are our customers for life.”
Mechanisms and Purpose: Sharma’s Philosophical Lens
Sharma picked up the thread with a philosophical reflection that set the tone for the discussion.
“One of the perennial problems with the world,” he said, “is mistaking means for ends and mechanisms for purpose.”
Tracing his journey from IBM’s Watson Research Center to startups and financial institutions, Sharma noted that the data industry has often fallen prey to its own mechanisms—building massive storage systems and analytics platforms without a clear sense of purpose.
He described four traditional purposes of data work:
1. Descriptive – understanding what exists.
2. Explanatory – revealing how systems behave.
3. Predictive – anticipating what might happen.
4. Prescriptive – using insight to optimize systems.
Yet, he warned, “People started misusing these definitions. Data became synonymous with what sits in a database. But data isn’t storage—it’s truth.”
“Storytelling,” he added, “should only be a mechanism to communicate that truth. Instead, storytelling became more important than veracity. The mechanisms took over.”
His disappointment was palpable: “If you’re not truthful, it’s a corruption of the soul. Somewhere along the way, we began valuing narratives over knowledge.”
Truth vs. Storytelling
Trower countered with a pragmatic view from inside government: “Yes, data is truth, but we rarely have perfect data. If you wait for perfection, you’ll never move forward.”
She argued that leadership often requires making decisions with incomplete information—something humans do every day. “So there has to be a give and take. Storytelling isn’t the enemy—it’s how you make insights meaningful.”
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Their exchange highlighted the tension at the heart of modern data practice: truth versus interpretation.
While Sharma defended purity of purpose, Trower insisted that progress depends on action—even if the dataset is messy.
When Data Tells Uncomfortable Stories
Tripathi pressed further: How do leaders handle *uncomfortable data*—the kind that challenges institutional narratives?
Trower acknowledged that such moments are inevitable. “Whether it’s spending millions on a tool that goes unused or discovering a breach attempt, the truth is often in the details—and not everyone wants to hear it.”
Her approach, she said, was to “tell the story online,” focusing on transparency and the mission rather than politics.
The January 2025 Transition: Chaos and Clarity
Revisiting the early 2025 transition, Trower described the period as “definitely chaotic.”
Transition teams arrived before inauguration, requesting access to data systems—a highly unusual step for an agency whose information is among the most sensitive in government.
Meanwhile, tax season loomed. “Filing season cannot fail,” she said. “Ninety percent of the U.S. budget depends on what the IRS collects.”
Maintaining trust, mission focus, and morale under such scrutiny, she said, was an enormous leadership test. “In inflection points, people look to leaders to see how they should lead. You have to steady the ship even when the water’s rough.”
Managing Truth and Trust Inside Organizations
Sharma reflected on his own career managing truth within organizations.
He likened data leaders to psychotherapists: “You have to help business leaders articulate what problem they’re actually trying to solve. Many don’t know.”
Often, he said, large organizations create silos that guarantee each division’s success—“even if the overall mission fails.”
That’s why he moved to a startup, where “you can have a clear conscience because you’re solving a real problem, end to end.”
He lamented a broader corporate culture where “leadership values action over knowledge” and middle managers are left to deliver results within flawed systems. “We have incredible professionals doing their jobs with integrity,” he said, “but the mission itself is misdirected.”
Innovation left on the table
Tripathi turned the conversation to innovation: given the IRS’s vast trove of taxpayer data, could more be done to improve lives?
Trower admitted she had long advocated for using predictive analytics to anticipate taxpayer needs, but privacy and perception posed barriers. “People already think of the IRS as Big Brother,” she said. “So even if we could help, do they want our help?”
She recalled proposing a spin-off entity focused on insights rather than enforcement. “The idea was quickly shut down,” she said with a smile. “But the potential is enormous if we can balance privacy with purpose.”
Underfunding, she added, has long constrained federal innovation. “The code at the heart of some IRS systems dates back to the 1960s,” she said. “It’s hard to pivot quickly when you’re running on legacy technology.”
What Other Countries Solved a Decade Ago
The panelists agreed that the U.S. lags behind in digital identity and interoperability.
Trower recalled attending international roundtables where peers from smaller nations described unified citizen portals. “They’d lean in when I talked about our challenges, then lean back and say, ‘We solved that 10 years ago.’”
Sharma added that transparency must precede optimization. “You cannot improve what you can’t see,” he said. “Some countries show citizens exactly where their tax dollars go. Until we achieve that visibility, we can’t claim progress.”
AI, Legacy Systems, and the Limits of Speed
Sharma cautioned against reckless modernization. “Speed isn’t always better,” he said.
He cited financial institutions still reliant on COBOL systems. “There are only a handful of COBOL programmers left. Some people now suggest using GenAI to rewrite COBOL into Java on the fly. It’s tempting—but dangerous.”
Trower nodded. “It only takes one keystroke to take production down. Then you get layers of bureaucracy to prevent it from happening again. It’s an overcorrection cycle we know too well.”
The CIO Role of 2030: From Department to Driver
Asked what she hopes CIOs will achieve by 2030, Trower’s answer was unequivocal: “I want CIOs to have more autonomy and recognition that IT is not a department over there—it *is* the business.”
She envisions a merger of business and IT functions, erasing the artificial divide that still hinders collaboration.
Sharma agreed. “Lines of business struggle to get their ideas to the IT division because mechanisms take over,” he said. “Vendors sell capabilities, not solutions, and IT buys them because IT has to succeed. But business asks, ‘What am I supposed to do with this?’”
That disconnect, he noted, explains why adoption rates for AI remain low. “We love the idea of a curious future,” he said, “but we don’t like to question whether it’s actually true.”
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The Human Element: Blue-Collar Data
In a striking turn, Sharma argued that the future of AI may depend on rediscovering the value of blue-collar knowledge.
“No abstraction in IT land can fully capture what a lineman or electrician does,” he said. “Eventually we have to deal with the physical world again—crumbling infrastructure, aging grids, real constraints.”
Trower linked that insight back to leadership. “Trust and truth still come down to people,” she said. “Technology can’t replace that.”
Guarding the Mission Against Misuse
An audience member asked how CIOs can counter public misinterpretation of data—especially when the media slices it “18 different ways.”
Trower’s answer was grounded in experience: “You don’t fight every story. You focus on your mission. Internally, you build trust so your people take their cue from you.”
Sharma added, “There’s no algorithmic solution to that problem. It’s moral philosophy. The organization must value truth even when it’s uncomfortable.”
Purpose, Truth, and the Moral Core of Technology
In closing, Sharma quoted a maxim that captured the session’s theme: “At the end of the day, technology—no matter how advanced—is a field of moral philosophy.”
Trower responded with her own mantra from a former IRS CIO: “Facts and data will set you free.”
Their exchange underscored what the panel had been circling all along: technology’s evolution may be exponential, but its success still depends on timeless virtues—truth, trust, and purpose.
As Tripathi summed up, “Strategy, IT, and data can no longer live in silos. To lead through inflection points, they must merge.”
And on that note, the conversation—equal parts warning and inspiration—came to a close, leaving the audience with a simple question:
In an era of AI and automation, will we let mechanisms define our purpose, or will purpose finally reclaim the mechanisms?