A CIO Panel Discussion at Optym LTL Convergence 2025
Moderator:
Kevin Major, Partner McKinsey & Company
Panel Members:
Harish Abbott, CEO & Co-Founder, Augment
Todd Florence, CIO, Estes
Rohit Lal, Executive VP of IT Strategy, Saia
Woody Lovelace, Senior VP & CIO, Southeastern Freight Lines
Technology transformation in LTL trucking is no longer theoretical. It’s operational, cultural, and deeply human.
That was the unifying message from a CIO panel at the Optym Convergence Conference, moderated by Kevin Major of McKinsey and featuring technology leaders from Estes, Southeastern Freight Lines, Saia, and Augment. While panelists brought different backgrounds and perspectives, their conclusions converged around a shared reality: modernization is less about tools and more about how organizations change around them.
Transformation Is Evolution, Not a Switch
One of the strongest themes to emerge was a rejection of “big bang” transformation thinking.
Several panelists emphasized that true transformation in LTL doesn’t happen overnight. Instead, it unfolds as a long-term evolution, one that must be owned by the organization, not outsourced or imposed.
Saia’s CIO Rohit Lal reflected that the most impactful transformation of his career wasn’t a single system or platform, but being embedded in the business long enough to see modernization from intent to execution to sustained change.
Estes’ CIO Todd Webb echoed that view, noting that many transformation plans look elegant on paper but collide with reality once ownership shifts from consultants to operators. In practice, what matters is not the plan itself, but how well technology and business stay aligned over time.
IT and the Business Are No Longer Separate
Across the panel, there was broad agreement that the historical separation between “IT strategy” and “business strategy” no longer works, if it ever did.
In LTL, technology does not support the business. Technology is the business. Every shipment, route, dock decision, and customer interaction depends on systems working in concert with operations.
Panelists described a growing trend toward tighter integration between IT and operations teams, with technologists embedded in the business and business leaders deeply involved in technology decisions. This shift has enabled faster decision-making, better prioritization, and higher trust, especially during periods of change.
Build vs. Buy: The Tipping Point Has Passed
When discussion turned to AI and emerging technologies, the panel took a notably pragmatic stance on build-versus-buy decisions.
While early generations of LTL systems were largely built in-house out of necessity, panelists agreed that the industry has reached a tipping point. The risk, cost, and distraction of rebuilding core systems from scratch now outweigh the benefits in most cases.
That doesn’t mean in-house development disappears. Instead, CIOs described a hybrid model:
- Buy platforms where capabilities are commoditized or rapidly evolving
- Build selectively where differentiation, proprietary data, or unique workflows matter
- Partner aggressively to accelerate time to value and share risk
AI amplifies this dynamic. As models, costs, and vendors evolve rapidly, locking into long-term commitments too early can create unnecessary exposure. Many panelists emphasized short contracts, pilots, and proofs of value to learn without overcommitting.
AI Is Real, but Production Is Hard
A recurring caution across the panel was the growing gap between AI prototypes and production-ready systems.
Panelists acknowledged that generative and agentic AI have dramatically lowered the barrier to experimentation. However, moving from a compelling demo to a reliable, auditable, and scalable solution is far more complex, especially in freight environments where errors propagate quickly across networks.
The consensus: AI value comes from integration, governance, and change management and not novelty.
The Real Constraint: Change Management
If there was one topic that generated near-universal agreement, it was this: change management determines ROI more than technology choices.
Panelists stressed that deploying new systems inevitably shifts work away from some roles and toward others. Organizations that plan for this — by retraining, repurposing, and communicating early — see materially better outcomes than those that delay hard conversations.
Several leaders highlighted that while frontline employees often adapt quickly to new tools, adoption stalls when leadership fails to fully embrace or support use the systems they’ve approved.
In other words, resistance at the top can be more damaging than skepticism on the dock.
Why “Good Enough” Beats “Perfect”
Another practical insight centered on perfectionism.
CIOs cautioned against delaying deployments in pursuit of flawless systems. In long-lived LTL environments, no system is ever truly finished, and waiting for perfection often erodes momentum, credibility, and business value.
A simple test emerged from the discussion:
- Is the solution better than what we have today?
- Does it deliver measurable return in its current state?
If the answer to both is yes, execution should move forward.
Where CIOs See the Biggest AI Impact
Looking ahead, panelists were cautious about making bold predictions, but aligned on the direction.
AI’s most meaningful impact is expected in:
- Reducing reliance on tribal knowledge
- Simplifying complex planning and decision-heavy roles
- Automating repetitive, low-value tasks
- Democratizing access to data and insights across the organization
Rather than replacing people, AI is seen as a force multiplier helping less-experienced employees perform at higher levels faster, while allowing seasoned leaders to focus on judgment, exceptions, and strategy.
A Shared North Star for LTL Technology
Despite differences in scale and structure, the panel converged on a shared north star: remove friction for employees and customers without losing operational control.
That means investing in systems that integrate end-to-end, keep humans in the loop, and evolve with the business, not ahead of it or behind it.
How This Aligns with Optym’s Perspective
The CIO panel’s conclusions closely mirror Optym’s long-held philosophy. Sustainable transformation in LTL requires:
- Deep, explainable optimization at the core
- AI layered thoughtfully on top to accelerate insight and execution
- Humans remained as decision-makers, not bypassed
Technology succeeds not when it dazzles, but when it fits seamlessly into how freight actually moves.
A Clear Message for LTL Leaders
For LTL executives navigating modernization today, the takeaway from this panel was unambiguous:
The hardest problems are no longer technical. They are organizational.
Those who invest as much in alignment, communication, and adoption as they do in software will be the ones who realize the full value of AI and optimization without disrupting the culture and people that make their networks run.
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