Google’s position in the artificial intelligence race is facing renewed scrutiny as reports suggest internal challenges at Google DeepMind may be slowing the development of its next-generation AI models. The company is competing against major rivals including OpenAI, Anthropic, and Meta, but delays, employee concerns, and rising costs are creating additional pressure on the technology giant.
According to a report by Axios, several current and former DeepMind employees linked slower AI model releases to factors including employee burnout, leadership concerns, and disagreements over Google’s military-related technology partnerships. Google has rejected claims that workplace morale issues are affecting its AI development process.
One of the major concerns involves Gemini 3.5 Pro, reportedly one of Google’s most advanced AI models currently under development. The model is said to be several months behind its expected timeline, although Google confirmed that it is being tested with selected partners and will be released publicly when it meets the company’s standards.
Instead of launching Gemini 3.5 Pro, Google recently introduced smaller AI models, including Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. These models are designed to provide faster responses, lower operating costs, and improved efficiency for developers and businesses.
While the smaller models focus on practical applications, their reception has been mixed. Some industry observers questioned whether Google’s latest releases demonstrate enough progress to compete with leading AI systems from rival companies.
The pressure on Google comes as the company continues to invest enormous amounts of money into artificial intelligence infrastructure. Alphabet, Google’s parent company, reported strong financial results, with total revenue increasing significantly. Google Cloud growth was boosted by rising demand for AI computing services and infrastructure.
However, the company’s increasing investment in data centers, specialized chips, and AI technology has also raised concerns among investors. Alphabet’s free cash flow declined as spending accelerated, while the company increased its expected capital expenditure for 2026 to between $195 billion and $205 billion.
Another challenge for Google is the loss of several high-profile AI researchers. Noam Shazeer, a key figure associated with Gemini development, reportedly left Google to join OpenAI. Meanwhile, John Jumper, a Nobel Prize-winning scientist and co-creator of AlphaFold, moved from Google DeepMind to Anthropic.
Some DeepMind employees reportedly believe Google has fallen behind competitors in certain areas of AI development. One concern raised was that the company focused heavily on protecting its traditional search business against AI competitors instead of moving faster into emerging areas such as AI coding assistants.
Google’s partnership with the US military has also created internal debate. Reports suggest that some employees have expressed concerns about the company’s agreement allowing the Pentagon to use Google technology for classified projects.
More than 600 Google employees previously signed a letter calling for restrictions on classified military AI work. Some former employees said the issue contributed to workplace tension and influenced their decision to leave the company.
Google, however, has pushed back against reports of a morale crisis. The company said employee departures have not increased significantly and stated that AI-related positions continue to attract strong interest from candidates.
Despite current challenges, Google remains one of the world’s most powerful technology companies with significant AI research capabilities, massive computing resources, and a global user base. The AI industry remains highly competitive, and leadership positions can shift quickly as companies release new breakthroughs.
The coming months will be critical for Google as it works to deliver advanced Gemini models, retain top researchers, and prove that its massive AI investments can translate into long-term market leadership. While temporary delays may not determine the company’s future, maintaining innovation speed and employee confidence will be essential in the rapidly evolving AI race.
