# Teradata, TTEC Redirect Compensation to Fund AI > Source: > Published: 2026-06-05 01:52:14.752290+00:00 # Teradata, TTEC Redirect Compensation to Fund AI According to Business Insider, cloud-software company Teradata told its **5,100** employees in January they will not receive annual salary increases in 2026, citing an internal memo from CEO **Steve McMillan** that says the company will reallocate that budget toward AI investments. Business Insider reports the memo includes the line, "We will fund this AI investment by reallocating the budget from 2026 annual salary adjustments," per McMillan. The outlet also reports that customer-experience firm **TTEC** has paused **401(k)** retirement contributions for US employees through the end of 2026, with internal communications saying the savings will support AI tools, training, and capabilities. Business Insider notes experts warn more companies could adopt similar measures as firms balance tighter budgets and rising AI spending. ### What happened According to Business Insider, **Teradata** informed its **5,100** employees in January that they should not expect an annual base-salary increase in 2026, citing an internal memo from CEO **Steve McMillan**. Per Business Insider, the memo states, "We will fund this AI investment by reallocating the budget from 2026 annual salary adjustments," attributed to McMillan. ### What happened (continued) Business Insider reports that Teradata's memo says employees may still be eligible for performance-based bonuses and equity awards, and that a company spokesperson told Business Insider the firm is "actively investing in AI to innovate its products and services." Business Insider and other outlets report that **TTEC** has suspended **401(k)** employer contributions for US employees through the end of 2026, with internal communications linking the pause to funding for AI tools, training, and capabilities. ### Editorial analysis - technical context Companies reallocating discretionary compensation pools toward technology investment is a recurring lever for funding strategic projects, particularly when capital budgets are constrained. For data and ML teams, this can translate into faster procurement of cloud GPU hours, commercial models, or vendor services but also tighter operational budgets for hiring and retention. ### Industry context For practitioners, the tradeoffs are concrete. Accelerated spend on compute, labeled data, or off-the-shelf AI platforms can shorten development timelines, yet organizations shifting fixed compensation may face higher churn risk among experienced engineers and data scientists, increasing downstream recruiting and onboarding costs. ### Context and significance Reporting frames these moves as part of a broader trend: public and private firms are increasing AI allocations while contending with macro pressures on margins. Business Insider reports experts warn more companies could follow suit, suggesting this is not an isolated budgeting choice but a potential pattern across cost-constrained firms racing to deploy AI capabilities. ### What to watch Observers should monitor whether companies that pause routine salary adjustments replace lost base compensation with larger bonus pools, equity grants, or targeted retention incentives, and whether those combinatory measures reduce voluntary turnover. Also watch vendor spend lines-rising contracts with cloud providers, model vendors, or AI consultancies would corroborate reallocated budgets reaching technical capacity rather than other line items. ### Industry context From a governance perspective, stakeholders will track disclosures in earnings calls and proxy filings for quantified AI spend versus personnel-cost changes. Labor groups and regulators may also pay attention if pauses in benefits or retirement contributions become widespread. ## Scoring Rationale Notable business decisions by established vendors change how AI programs are financed and will matter to practitioners managing budgets, procurement, and retention. The story is company-level rather than a technical breakthrough, so impact is meaningful but not frontier-changing. Practice with real FinTech & Trading data 90 SQL & Python problems · 15 industry datasets [Active Verified Users by Income TierEasy](/problems/sql/active-verified-users-by-income) [Technology Stocks with High BetaMedium](/problems/sql/technology-stocks-with-high-beta) [Portfolio Performance ScorecardHard](/problems/sql/portfolio-performance-scorecard) 250 free problems · No credit card [See all FinTech & Trading problems](/problems/datasets/fintech)