Enterprise tech pricing is at an inflection point. On 23 January 2026, Mphasis CEO Nitin Rakesh cautioned peers against a reckless price-cutting race. He stressed that an AI pricing strategy must hinge on delivery reinvention, not simple discounts. Consequently, service leaders face a pivotal choice: protect margins through smarter automation or surrender value in a bid to win deals. This article unpacks the warning, reviews the supporting data, and explores how providers can navigate the shift while measuring the IT services AI impact.

CEO Warning Echoes Loud

Rakesh’s message was direct. “The race to the bottom is a very risky race,” he told analysts. Furthermore, he argued that clients still accept hourly billing but now demand AI-powered outcomes. Therefore, vendors must redesign workflows, slash manual effort, and capture productivity gains within a disciplined AI pricing strategy. Nevertheless, the temptation to cut rates persists, especially as procurement teams benchmark AI efficiency savings.

These remarks followed Mphasis’s Q3 FY26 results. Revenue reached US$451 million, growing 2.6% sequentially. Operating margin held near 15.2%. However, management admitted day-to-day “run” operations face heightened automation pressure. Consequently, price wars could erode profitability if vendors misread the moment.

Rakesh’s warning sets the stage. However, market context reveals why the guidance matters.

Market Context Evolves Fast

Over the past year, Mphasis and rivals repositioned as AI-led partners. Additionally, clients accelerated pilots that embed code copilots and observability agents into software pipelines. Moreover, OECD studies show enterprise AI deployments can recover costs within months when volumes are high. In contrast, legacy contracts continue to reward headcount, dampening incentives to automate.

Pressure intensifies as global consultancies publicize concessions. For example, PwC confirmed selective fee cuts where AI trimmed staff hours. Consequently, buyers expect similar generosity from offshore vendors. An ill-designed AI pricing strategy could trap providers in margin-sapping negotiations.

The backdrop underscores the broader IT services AI impact. However, numbers provide the sharpest signal.

Financial Numbers Underscore Reality

Hard data illustrates the delicate balance between growth and margin.

• Q3 FY26 revenue: US$451 million, up 7-12% year-on-year.
• Operating margin: 15.2%, stable despite wage inflation.
• Billing mix: 46.8% time-and-materials, 44.8% fixed price, 8.4% transaction based.
• FY25 new TCV: US$1.27 billion, 55% branded “AI-led.”

Furthermore, the company highlighted an expanding AI pipeline across banking, insurance, and logistics. Nevertheless, Rakesh warned that sustained margins depend on outcome contracts, not cheaper rates. Therefore, the financial snapshot reinforces why a disciplined AI pricing strategy matters.

These figures reveal topline resilience. However, client behavior is shifting even faster.

Client Expectations Shift Rapidly

Buyers now benchmark vendors on productivity, not bodies. For instance, some clients track GitHub commit velocity and defect escape rates. Additionally, they use copilots to scrutinize development cycles. Consequently, vendors must prove throughput gains upfront.

Meanwhile, CIOs push for shared incentives during renewal talks. They request dual-track models: traditional time-and-materials for innovation sprints and transaction pricing for stable operations. Such expectations intensify the IT services AI impact on contract governance.

Therefore, providers need transparent metrics, automated observability, and value dashboards. Embedding these capabilities allows a confident AI pricing strategy that defends margins while rewarding outcomes.

Clear measurement frameworks reposition vendors as partners, not cost centers. However, competitors already test different tactics.

Competitive Pricing Responses Emerge

Global consultancies present contrasting approaches. PwC openly shares savings when AI tools compress audit hours. Deloitte pilots usage-based analytics deals. Moreover, Indian majors like Infosys and Wipro promote platform subscriptions that bundle AI accelerators.

In contrast, some mid-tier firms still rely on blanket discounts to secure renewals. Such tactics risk a downward spiral. Nevertheless, selective concessions can support strategic logos when coupled with intellectual property upsell.

Mphasis positions its NeoIP platform as an antidote. The firm anchors proposals on proprietary accelerators, maintaining pricing power through differentiated IP. Consequently, a balanced AI pricing strategy blends modest givebacks with premium platform fees, limiting exposure to commoditization.

Rival moves show multiple playbooks exist. However, strategic alignment is essential.

Strategic Path Forward Defined

Service leaders can follow a structured roadmap.

1. Re-engineer delivery to cut manual effort by 30-50% using agents and copilots.
2. Shift stable “run” work toward transaction pricing with clear baselines.
3. Monetize accelerators through subscription add-ons.
4. Ring-fence innovation sprints under time-and-materials with outcome KPIs.
5. Upskill teams via targeted learning pathways and certifications.

Professionals can enhance their expertise with the AI Executive Essentials™ certification. Additionally, platform teams should embed cost observability to justify every line item. Consequently, a cohesive AI pricing strategy emerges that captures value while satisfying procurement.

This roadmap aligns commercial models with delivery realities. However, stakeholders must weigh broader implications.

Implications And Next Steps

For investors, margin trajectories hinge on who captures AI productivity. Furthermore, outcome-oriented vendors may expand EBITDA despite rate pressure. For CIOs, transparent metrics reduce vendor-client friction and accelerate modernization. Additionally, employees gain opportunities in orchestration and oversight, offsetting reduced manual work.

The IT services AI impact will reshape skills demand. Consequently, proactive reskilling remains vital. Vendor ecosystems that offer structured learning, such as the linked certification, build credibility and retention.

Stakeholders must act before pricing debates harden into expectations. Therefore, adopting a resilient AI pricing strategy now preserves choice and margin later.

These implications highlight the stakes. However, effective execution determines wins and losses.

Key Takeaways Recap

• Aggressive discounts risk margin erosion.
• Platform IP can offset rate pressure.
• Transparent metrics enable outcome pricing.
• Certifications accelerate workforce readiness.

Consequently, the market favors vendors that align delivery, talent, and commercials.

Overall, an intentional AI pricing strategy offers the best defense against a destructive price war. The next section summarizes actionable steps.

Actionable Final Checklist

1. Map automation levers across portfolios.
2. Convert “run” contracts to transaction models.
3. Bundle accelerators as premium add-ons.
4. Measure productivity with real-time dashboards.
5. Upskill managers through executive AI programs.

Following this checklist embeds resilience within proposals and sustains differentiation.

Consequently, firms that execute early gain pricing leverage. Meanwhile, laggards face commoditization.

The stage is set for decisive moves in 2026.

In conclusion, Rakesh’s warning crystallizes a broader industry crossroads. Vendors can chase unsustainable discounts or craft a disciplined AI pricing strategy that rewards automation and IP. Moreover, transparent metrics and outcome contracts convert AI efficiency into mutual value, mitigating the IT services AI impact on margins. Forward-thinking leaders should embed automation, measure relentlessly, and invest in talent. Consequently, enterprises that align these levers will outpace the market. Explore the highlighted certification to deepen strategic insight and lead the pricing transformation.