In this economy of mixed signals—from shifting trade dynamics to inflation and varying growth estimates—capitalizing on the moment’s opportunities can sometimes feel like a complex balancing act. Standing at the edge of a new era, executives everywhere are wondering how to align the need to cut costs, boost efficiency and simultaneously navigate the transformative potential of emerging technologies.
As they try to understand how to increase resiliency and anti-fragility, C-level executives have exhausted traditional approaches to increasing operational efficiency and optimizing cost. The old cost levers—outsourcing, vendor consolidation and headcount—reduce costs but don’t improve capabilities or accelerate business outcomes, and come at the price of morale. How, then, can organizations do more with less?
Inevitably, a growing number of leaders are coming to see that the uncertainty and urgency of the moment mean that AI is no longer a gamble, but rather a strategic imperative. AI has emerged as a fundamentally new kind of strategic lever, capable of driving sustainable efficiency gains by transforming how work gets done — all while augmenting, rather than replacing, human capability.
Right now is the time for leaders to take a closer look at how AI is radically redefining efficiency in three areas—multiplying team productivity, driving cost takeout at scale and compounding enterprise velocity.
AI, the force multiplier
There’s a reason that 2025 is AI’s year of ROI. This moment marks a turning point, in large part because of what I’ll call AI’s “force multiplier” effect.
As today’s economic climate renders traditional models for boosting productivity unsustainable, leaders face demands to do more, often with fewer people. In the face of this dilemma, forward-thinking executive teams have started to deploy agentic AI systems that embed into day-to-day workflows and significantly amplify human output. Generating a measurable force multiplier effect, agentic AI systems empower team members without replacing them, increasing productivity by initiating, assisting and completing tasks alongside human teams.
The momentum of agentic AI is clear. Deloitte reports that the majority of business leaders see agentic AI as the most important GenAI development, while Gartner predicts it will autonomously handle at least 15% of day-to-day work decisions by 2028—up from 0% in 2024.
Agentic AI systems are beginning to plan, decide and act independently across enterprise workflows, and the productivity amplification has been remarkable. While IBM’s $3.5 billion in productivity gains show what’s possible with deep investment, an Accenture survey found that organizations more broadly are seeing a 2.4x boost in productivity by integrating AI into core processes.
If a single employee empowered with a powerful AI assistant can do the work of several—whether writing code, drafting reports, serving customers or managing operations—the mandate for leaders to harness this multiplier effect becomes clear. Start small, think big, invest in training and reimagine processes with an “AI + human” design.
AI-driven cost optimization: don’t downsize, accelerate velocity and empower teams
At moments of mounting economic pressure, the instinct to turn to classical cost-cutting levers is natural. But in 2025, a new concept of “lean” has crystallized. One-time cuts that don’t improve capability stop being the cautious approach when competitors are supercharging conventional levers through strategic investment in AI.
By analyzing usage patterns, codebases, infrastructure and business logic, AI systems are uncovering inefficiencies, automating manual effort and optimizing resources. In doing so, they’re turning traditional levers across people, processes and platforms into engines of structural, sustainable cost takeout.
What’s more, by consolidating redundant applications, optimizing cloud spend through real-time FinOps, and automating routine workflows, these efficiencies don’t just remove bloat—they often improve the systems left behind. Technical debt shrinks. Interoperability improves. The organization truly becomes leaner and more responsive.
The results have been game-changing. A 2025 WEF report shows that early adopters of AI tools and processes have realized cost savings of 13%. High productivity growth companies are now realizing a 4.5% gain in cost-efficiency ratio compared to peers.
In an AI-native era, it’s become clear that managing cost isn’t about cuts, but rather about rethinking cost itself. By continuously analyzing operations and recommending optimizations, AI enables us not just to do more with less—but to do more, much better, with less.
The velocity advantage
In the end, our current business climate is defined not only by rising expectations, but also by shrinking timelines. Already, the edge increasingly belongs to those who can move much faster without sacrificing quality.
For early adopters, it’s hard to overstate just how much AI has rewritten the software development lifecycle (SDLC) to meet this urgency. AI collapses time-to-value by transforming how products move from backlog to launch—validating requirements in real time, auto-generating test cases, accelerating deployment through DevOps orchestration and assisting with code review and refactoring.
To drive real enterprise velocity, business leaders should focus on three key accelerators within the SDLC. These include removing manual chokepoints through AI-driven automation, reducing technical debt by increasing automation across testing, development, and deployment, and accelerating outcomes by delivering new technology initiatives faster to unlock earlier, more consistent ROI.
When organizations approach AI-SDLC strategically, the result has been dramatically faster release cycles, fewer bugs and higher-quality code. IBM reports that generative AI can cut time-to-market by 15% and reduce bugs by the same margin. Meanwhile, PwC says that leading adopters launch products 73% faster and Forrester finds AI boosts developer productivity by up to 50%.
Speed compounded
While AI-SDLC boosts core development metrics, the real power of this SDLC transformation lies in that it’s not only technical. Leaders are seeing that this acceleration also builds organizational velocity, shortening feedback loops, reducing project overhead and accelerating decision-making at every layer. What’s being witnessed is speed done intelligently, compounding.
As AI redefines efficiency for this economic moment, it’s this sort of compounding of value that gets to the core of the opportunity that’s emerging for business leaders. In 2025, AI is delivering real ROI because the efficiency flywheel has fully transformed the bold path into the prudent path. Your AI transformation can no longer be your bet on the future—it’s your clearest strategy for the present.
