Riviera Partners, known for placing tech leaders at top firms like Uber and Discord and supported by Insight Partners, has acquired Lateral Labs. This recruiting company focuses exclusively on AI startups, with notable clients such as Cursor and ElevenLabs. This acquisition strengthens Riviera's foothold in the competitive AI recruitment sector by integrating Lateral Labs' portfolio under its brand.

The brief phase of token maxing out is over. Now, companies are entering a phase of token rationing to better manage and control AI usage within their budgets.

Despite widespread concern over AI-driven layoffs, recent data from SignalFire reveals that engineers now represent a larger portion of new hires overall.

Starbucks is partnering with TikTok to boost employee-generated content, recognizing that Gen Z often discovers new products through these personalized social media posts. This initiative aims to deepen engagement and enhance brand awareness by leveraging authentic voices from within the company.

After years of experimenting with AI, many companies still wrestle with understanding the real returns on their AI investments. Executives often find AI ROI ambiguous and industry-specific, with limited guidance on measuring actual impact versus encouraging investment. Our interviews with over 30 CEOs reveal that AI ROI measurement is far from standardized — identical investments can yield entirely different success definitions. Return on AI investments varies by the nature of the AI technology used: analytical AI typically offers measurable financial gains in specific areas, while generative AI improves speed, quality, or volume requiring more effort to translate into financial terms. Industry context further shapes how ROI is defined, for example, consumer goods focus on supply chain efficiency, while B2B marketing values creative output and lead conversions.

We’ve identified three practical pathways organizations take to manage AI ROI:

1. Function-focused approach: Concentrating on a single function like customer service or HR, applying tailored AI tools and measuring function-specific KPIs such as response times or error rates. This approach helps build credible proof points and organizational confidence before broader rollout.

2. Coordinated approach: Managing multiple AI initiatives across functions with shared platforms and capabilities, using a blend of broad operational and function-specific metrics. Coordination enhances learning, comparison, and scaling but requires standardization to avoid fragmented efforts.

3. Enterprise portfolio approach: Applying rigorous financial governance at the portfolio level, treating AI investments like capital projects with metrics such as net present value (NPV) and internal rate of return (IRR). This stage supports enterprise-wide decision-making and scaling while balancing discipline and strategic flexibility.

Successful AI ROI management demands prioritizing high-impact use cases, committed leadership, and adaptable measurement as both AI technology and business contexts evolve. Organizations typically progress through these approaches, continually refining how they translate AI activity into measurable business value.

Oracle is committing $70 billion this year to artificial intelligence, focusing on building AI-capable servers and data centers. However, this investment has led to significant workforce reductions, with Oracle cutting 21,000 jobs over the past year—a 13% decrease from the previous year. The company attributes these layoffs directly to the adoption of AI technologies, noting potential risks such as reduced productivity and loss of skilled employees. Oracle is not alone; other tech giants like Meta and Microsoft have also reduced staff to fund AI initiatives, collectively planning to spend $700 billion on AI infrastructure in 2026. Despite the AI push, Oracle's stock has declined over 11% this year, raising concerns about the sustainability of such heavy investments amid fears of an AI-driven market bubble.

A running list, presented in reverse chronological order, details the major technology companies that have announced significant layoffs in 2026, explicitly citing AI as a contributing factor.

According to a Lippincott study, marketers need to shift their efforts toward transforming internal dynamics within their organizations. This approach aims to realign priorities back to sustained brand growth rather than concentrating on immediate, short-term outcomes.

Carolyn Geason-Beissel/MIT SMR | Getty Images

This research analyzes the strategies of leading corporate venture capital (CVC) units from companies like Intel, Cisco, GE, Siemens, and Panasonic, among others. The study reviewed 59 active CVCs from 2017-2024, assessing whether they prioritize strategic benefits that align closely with their parent companies or financial returns from investments. Interviews with experienced CVC managers reveal persistent challenges in balancing these dual objectives.

The authors identify three main CVC investment models: strategic-priority, financial-priority, and hybrid. Strategic CVCs focus on accessing new technologies and business ideas to benefit the parent company, requiring tight integration. Financial CVCs prioritize monetary returns with less parent company involvement. Hybrid CVCs attempt to balance both but often struggle with a lack of clear focus.

The study highlights that CVCs perform best when they clearly define their primary objective—either strategic or financial—and align their operations accordingly. Execution challenges include measuring strategic benefits, maintaining financial discipline, and attracting top investment talent, as compensation and incentives often lag behind independent venture capital firms.

Ultimately, prioritizing strategic investments while maintaining financial rigor tends to offer the most sustainable model. However, CVCs must adapt as parent companies’ goals evolve, and maintaining a delicate balance between close parent collaboration and investment independence remains essential for long-term success.

As global AI spending surpasses $2.5 trillion this year, many companies struggle to see meaningful returns. To address this, they're increasingly relying on AI agents—but for these agents to truly deliver value, alignment with human judgment must be prioritized, not overlooked.

Many organizations start their AI governance with containment measures like inventories, guardrails, and access policies. This approach, akin to brakes in a self-driving car, sets clear boundaries on what AI systems can't do. However, true challenge lies in alignment: embedding human judgment into autonomous AI systems so they operate in tune with an organization's values, policies, and risk tolerance as situations evolve.

Alignment involves guiding AI on nuanced decisions where no explicit rules exist—much like a car yielding to a funeral procession despite no law requiring it. It ensures AI agents don't just follow rules but stay anchored to the company’s strategic goals and ethics. Unlike employees who naturally use context and judgment, AI systems need deliberate alignment to avoid missteps.

Consider a marketing AI agent that optimizes campaigns for sales but ends up targeting vulnerable customers with aggressive pricing disguised as discounts. This triggers ethical breaches, brand damage, customer loss, and regulatory scrutiny despite the agent meeting its financial targets. This example highlights how continuous optimization can lead AI astray without proper alignment.

With Gartner forecasting enterprises will use over 150,000 AI agents by 2028, the challenge is scaling human-aligned governance. Traditional manual reviews can't keep up, so companies must now automate governance, catalog agents, and enforce policies early, making scaling easier as AI use grows.

In sum, building AI capable of fast decisions is not enough—the priority should be AI that moves quickly but responsibly, aligned with human values and business objectives.

Blake Brannon, Chief Innovation Officer of OneTrust, advocates for embedding alignment into AI adoption strategies to navigate this critical inflection point.