The departures of Tony Wu and Jimmy Ba reduce xAI’s founding team by half, pointing to mounting internal and competitive pressures as Elon Musk races to close the gap with OpenAI and Anthropic.

Tony Wu and Jimmy Ba, two co-founders of Elon Musk’s artificial intelligence venture xAI, have resigned from the company less than three years after helping to launch it. The announcements, made in separate posts on X, mark the latest leadership changes at the firm and leave it with six of its original 12 co-founders.

Neither Wu nor Ba publicly stated their reasons for stepping down or outlined immediate next steps, though both expressed gratitude to Musk in their messages.

Their exits come at a pivotal moment for xAI, which was founded in 2023 as Musk’s direct challenge to OpenAI, the company he co-founded and later publicly criticized over its direction and governance. Since its launch, xAI has sought to position its Grok model — integrated into Musk’s social media platform X — as a more open and less constrained alternative to competing large language models.

Reported internal tensions

The Financial Times reported that Ba’s resignation followed tensions within xAI’s technical team over pressure to improve model performance as Musk pushes to narrow the gap with industry leaders such as OpenAI and Anthropic.

Performance benchmarks have become central in the generative AI race. Companies compete aggressively on reasoning ability, coding accuracy, multimodal capabilities, and inference speed. Any perception of lagging progress can affect valuation, partnerships, and investor appetite.

If internal friction emerged over engineering timelines or product readiness, it would reflect the broader strain facing AI startups attempting to scale foundational models at breakneck speed while competing against firms with deeper capital reserves and established research ecosystems.

Ba, a well-known academic in machine learning and co-author of the widely cited Adam optimization algorithm, brought significant technical credibility to xAI at its inception. Wu also played a key role in the company’s early engineering development. Their departures remove two influential voices from the core research group at a time when execution speed is critical.

High-capex environment

Days before the resignations became public, SpaceX announced plans to purchase xAI in a transaction that Musk said would create a combined entity valued at $1.25 trillion. The merged structure is reportedly intended to go public later this year, with proceeds aimed at financing large-scale infrastructure projects, including ambitions to deploy data centers in space.

The proposed integration signals how capital-intensive Musk’s AI strategy has become. Training frontier models requires vast computational resources, often involving tens of thousands of high-end GPUs, advanced cooling systems, and long-term energy contracts. Infrastructure spending now defines competitive positioning in AI as much as algorithmic breakthroughs.

By folding xAI into SpaceX’s orbit, Musk appears to be consolidating capital, engineering capacity, and long-term financing mechanisms under a single corporate umbrella. SpaceX’s strong private-market valuation and track record of raising large funding rounds could provide xAI with more stable access to capital than a standalone startup structure.

Yet such consolidation can also intensify internal performance expectations. As investor scrutiny grows — particularly ahead of a potential public listing — pressure to demonstrate technical parity with rivals may increase.

OpenAI, Anthropic, and Google DeepMind have widened the performance envelope of large language models over the past year, introducing models capable of advanced reasoning, coding, video generation, and real-time multimodal interaction. Each firm has secured major enterprise and government partnerships.

Grok’s integration into X gives it a built-in distribution channel to hundreds of millions of users for xAI. However, distribution alone does not guarantee leadership in benchmark performance or enterprise adoption. Corporate customers typically evaluate AI systems on reliability, safety controls, latency, and integration flexibility — areas where incumbents have invested heavily.

The departure of founding researchers could prompt questions about continuity in xAI’s core research agenda. Founders often anchor technical culture, long-term research direction, and hiring pipelines. Replacing that institutional knowledge requires careful management, particularly in a sector where talent mobility is high, and competition for senior AI researchers is intense.

Strategic inflection point

Musk has repeatedly framed AI as central to his broader industrial ambitions, linking it to autonomous vehicles, robotics, and space infrastructure. The decision to align xAI more closely with SpaceX suggests a strategy built around vertical integration — controlling hardware, compute, data pipelines, and application layers within a unified ecosystem.

That strategy carries significant upside if execution aligns. It also raises governance and operational complexity, especially if the combined entity proceeds toward a public listing at a multitrillion-dollar valuation target.

For now, xAI remains in active development mode, continuing to iterate on Grok and expand its infrastructure footprint. The loss of half its founding team does not necessarily derail that trajectory, but it signals internal recalibration at a time when the global AI race is accelerating.

In frontier AI, leadership stability, technical momentum, and capital scale often determine which firms define the next generation of platforms. In the coming months, xAI will be proving whether it can maintain research velocity and organizational cohesion as it enters a more demanding phase of competition and financial scrutiny.

Dassault’s historic share price plunge points to investor anxiety that slowing software revenues and modest guidance may undermine its long-term 7% annual growth ambition.

Shares of Dassault Systèmes plunged as much as 21% in early Wednesday trading — the steepest intraday decline in the company’s history — after fourth-quarter results exposed a marked slowdown in its core software business and a cautious outlook for 2026.

The Paris-listed stock was briefly suspended at the open due to volatility before trimming losses to around 18% by mid-morning in London.

Investors had expected resilience from one of Europe’s most prominent enterprise software groups, known for its dominance in industrial design, 3D modelling, and product lifecycle management software used by aerospace, automotive, defense, and life sciences companies. Instead, the company delivered flat full-year revenue and a contraction in its most critical segment.

Software revenue fell 5% in the fourth quarter. For the full year, total revenue came in at 6.24 billion euros ($7.43 billion), below the 6.3 billion euros forecast by analysts surveyed by LSEG. Annual software revenue reached 5.64 billion euros, showing little growth.

Given that software accounts for the bulk of Dassault’s income — and underpins its high-margin, recurring revenue model — the deceleration struck at the core of its investment case.

Guidance compounds concerns

Adding to the unease, the company guided for revenue growth of 3% to 5% in 2026. That range was widely viewed as conservative, especially in light of Dassault’s previously stated ambition to grow at least 7% annually between 2024 and 2029.

Analysts at UBS noted that achieving that target now implies the company would need to deliver 8.2% to 8.9% annual growth from 2027 to 2029 to compensate for weaker early-year performance. That significantly raises execution risk.

In effect, management is asking investors to accept near-term softness while maintaining confidence in accelerated medium-term expansion.

Chief Executive Pascal Daloz framed the results as part of a longer strategic shift. In a statement, he said Dassault “will lead the Industrial AI transformation” through its 3D UNIV+RSES platform, positioning artificial intelligence as central to the company’s next phase of growth.

“This is not a short-term goal,” Daloz said. “It is a long-term commitment to redefine how industries innovate, operate, and compete.”

He added that 2025 and 2026 would focus on disciplined execution and aligning resources around strategic priorities.

The emphasis on alignment and execution suggests internal recalibration — potentially tighter cost controls, portfolio optimization, or reprioritization of R&D spending — as management seeks to stabilize performance.

The broader AI backdrop

The sharp drop in Dassault’s stock is not happening in isolation. Software companies have been at the center of heightened volatility after new AI tools from Anthropic triggered a sector-wide sell-off last week. Investors are reassessing the sustainability of traditional software-as-a-service (SaaS) models in an era where AI-native systems may reshape workflows and pricing structures.

Aoifinn Devitt, senior investment adviser at Moneta, described the environment as a “SaaS apocalypse” trade, referring to mounting investor concerns about last year’s high-growth software winners.

“There is really a concern right now around some of those winners that led the charge last year,” Devitt said on CNBC’s “Squawk Box Europe.”

The concern is structural rather than cyclical. If generative AI tools reduce reliance on traditional design, modelling, or simulation software — or compress pricing power — established vendors could face slower growth and margin pressure.

Dassault argues the opposite: that AI enhances the value of digital twins, 3D modelling, and simulation by making them more predictive and integrated across industrial ecosystems. Its 3D UNIV+RSES platform integrates design, manufacturing, supply chain, and lifecycle data into unified virtual environments, an approach that management believes is uniquely positioned for industrial AI.

However, investors appear to want clearer evidence that AI investments are translating into accelerating revenue rather than elevated costs.

Macro pressures and customer exposure

Dassault’s client base adds another layer of challenge. Its customers include major aerospace, automotive, and industrial manufacturers — sectors sensitive to economic cycles, capital expenditure budgets, and geopolitical uncertainty.

Higher borrowing costs in recent years have weighed on corporate investment. If industrial clients delay large digital transformation projects or software upgrades, revenue growth can stall quickly.

In addition, the transition from on-premise licenses to cloud-based subscriptions, while beneficial long-term, can create temporary headwinds in revenue recognition and customer migration. Investors may be questioning whether this transition is progressing smoothly enough to offset broader demand softness.

Unlike pure-play SaaS firms focused on office productivity or CRM tools, Dassault’s growth depends heavily on complex, multi-year industrial programmes. That can make earnings more stable in downturns but slower to rebound when sentiment improves.

Valuation reset

The scale of Wednesday’s sell-off suggests a broader valuation reset rather than a reaction to a single quarterly miss. Enterprise software companies have commanded premium multiples based on predictable recurring revenue and strong operating leverage. When growth slows, those premiums can contract sharply.

If revenue growth remains in the low single digits over the next year or two, investors may assign a lower earnings multiple until clearer acceleration emerges.

At the same time, the company’s balance sheet and market position remain solid. Dassault continues to generate substantial cash flow and holds a strategic footprint in mission-critical industrial software niches with high switching costs.

The key question is whether AI becomes a growth catalyst or a disruptive force that intensifies competition and compresses margins.

Management now faces a dual challenge: stabilizing short-term performance while convincing markets that its Industrial AI strategy can drive sustained, above-market growth later in the decade.

Execution in 2025 and 2026 will be critical. If subscription momentum strengthens, cloud adoption accelerates, and AI-enabled products gain traction among industrial clients, investor confidence may recover.

If not, Wednesday’s historic decline could mark the beginning of a more prolonged reassessment of one of Europe’s flagship technology names.

Tony Elumelu, chairman of UBA Group, has provided a detailed explanation of why entrepreneurs frequently encounter stringent conditions when seeking loans from commercial banks, arguing that regulatory tightening — rather than unwillingness by lenders — sits at the core of the problem.

Speaking at the 49th Governing Council meeting of the International Fund for Agricultural Development (IFAD) in Rome, Elumelu said commercial banks operate within strict prudential frameworks that limit the amount and type of risk they can assume, particularly in lending to small and medium-sized enterprises (SMEs).

“The issue of finance, I wear a commercial bank hat. There’s a limit to what they can do in providing the kind of risk capital that SMEs or entrepreneurs need,” he said.

His remarks come amid evolving credit dynamics in Nigeria’s banking sector, where lenders are cautiously expanding credit even as repayment risks rise and borrowing costs remain elevated.

The regulatory capital constraint

Commercial banks are bound by capital adequacy requirements set by regulators. These rules require banks to hold sufficient capital against risk-weighted assets, including loans. When banks extend credit to borrowers considered high risk — such as early-stage SMEs without collateral or stable cash flows — the regulatory capital charge increases.

“If you don’t do that, there’s a charge on the bank’s capital, but people don’t understand this. So oftentimes they blame financial institutions, but the regulatory environment is tightening; it will not allow banks to provide the kind of money,” Elumelu said.

In practical terms, unsecured lending or loans backed by weak collateral raise the risk weighting on a bank’s balance sheet. That forces the institution to set aside more capital, reducing its ability to lend elsewhere and potentially affecting shareholder returns.

In an environment where regulators are focused on financial system stability, particularly after years of economic volatility, banks are under pressure to maintain healthy capital buffers and keep non-performing loan ratios under control.

Interest rate and rising defaults shape lending behavior

Recent data from the Central Bank of Nigeria (CBN) reinforces the cautious stance. In its Q4 2025 Credit Conditions Survey, the CBN reported improved credit availability across major segments, but also noted rising defaults among households and businesses.

Defaults increased across secured, unsecured, and corporate loans during the quarter. That trend naturally leads banks to tighten risk assessment processes, demand stronger collateral, and price loans more conservatively.

For corporate borrowers, conditions were mixed. Loan spreads narrowed for small businesses, large private non-financial corporations (PNFCs), and other financial corporations, suggesting improved pricing in those segments. However, medium-sized PNFCs faced widening spreads, reflecting tighter credit terms.

This divergence highlights a key dynamic: while credit may be expanding in aggregate, access and pricing vary significantly depending on perceived risk.

High lending rates remain a major constraint. Commercial loan rates currently range between 29 percent and 36 percent. At such levels, debt servicing can consume a large portion of operating cash flow, particularly for SMEs in sectors already grappling with foreign exchange volatility, energy costs, and inflationary pressures.

According to CBN data from early 2025, 75 percent of businesses identified high interest rates as their most pressing operational challenge.

For banks, elevated rates reflect both monetary policy tightening and embedded credit risk. For entrepreneurs, they represent a barrier to expansion, investment, and hiring.

The policy dilemma is clear: interest rates are kept high to manage inflation and protect the currency, yet that same policy stance raises the cost of capital for the private sector.

Why SMEs face structural disadvantages

SMEs typically lack the audited financial statements, long credit histories, and asset bases that larger corporations can offer. Many operate in semi-formal structures, making risk assessment more complex.

From a banking standpoint, this raises due diligence costs and default probabilities. When combined with regulatory capital charges, the result is conservative underwriting standards.

Elumelu acknowledged this structural limitation.

“There’s a limit to what they can do,” he said, underscoring that commercial banks are not designed to provide early-stage venture-style capital.

Elumelu also questioned whether development finance institutions (DFIs) are effectively filling the financing gap.

“You go to some development financial institution, they will ask for an arm and a leg. Then you start wondering, how would these young entrepreneurs provide this collateral?” he said.

DFIs were created to support sectors and businesses underserved by commercial banks. However, procedural bottlenecks, documentation requirements, and collateral demands often mirror the constraints found in traditional banking.

This leaves many entrepreneurs navigating a financing ecosystem where neither commercial lenders nor public development institutions fully absorb the risk inherent in start-up ventures.

The Tony Elumelu Foundation as an alternative capital

Elumelu cited these challenges as the motivation behind establishing the Tony Elumelu Foundation (TEF), which provides $5,000 in non-refundable seed capital to selected entrepreneurs.

Unlike bank loans, these grants do not require collateral or repayment. They are designed to provide risk capital at the earliest stage of business development — precisely the type of funding that regulated banks cannot extend without capital implications.

The model separates philanthropic risk-taking from commercial banking operations, acknowledging that different types of capital serve different functions in an entrepreneurial ecosystem.

Elumelu’s comments also intersect with broader economic conditions. Nigeria’s banking sector is navigating rising capital requirements, tighter global financial conditions, and domestic macroeconomic adjustments.

While the CBN survey shows improved credit availability, the rise in defaults signals lingering stress within the economy. Banks must balance credit growth with asset quality preservation.

The trade-off has been delicate for policymakers. Overly loose regulation risks financial instability. Excessively tight regulation may suppress entrepreneurial growth and job creation.

Elumelu framed the issue as one requiring government action beyond the banking sector.

“So I take to advocacy, I pray to government, create the enabling environment, support the young entrepreneurs. And indeed, in some ways, it’s working,” he said.

An enabling environment includes stable macroeconomic policy, reliable infrastructure, predictable taxation, and legal reforms that reduce business risk. Lower systemic risk would, in turn, reduce credit risk and capital charges for banks.

The broader economic implications

SMEs account for a significant share of employment and economic activity in Nigeria. Constrained access to affordable credit, therefore, has implications beyond individual businesses — it affects growth, innovation, and poverty reduction.

The situation reflects a structural challenge rather than a simple funding shortage. Regulatory prudence, rising defaults, and high interest rates converge to limit banks’ appetite for risk capital.

Elumelu’s remarks highlight a core tension in emerging markets: safeguarding financial stability while expanding access to capital for businesses that drive inclusive growth.

Until that balance is recalibrated through policy reform, innovative financing models, or targeted public-private partnerships, entrepreneurs are likely to continue facing stringent lending conditions, even as aggregate credit data shows gradual improvement.