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DeepSeek Gives European Companies A Chance To Close The AI Gap

by THEFUTURE.TEAM

February 3, 2025

IIn the world of artificial intelligence, the rise of DeepSeek is offering European companies a significant opportunity to level the playing field. Hemanth Mandapati, the CEO of the German startup Novo AI, was among the first to shift from OpenAI’s ChatGPT to the Chinese AI model, DeepSeek, just two weeks ago. Speaking at the GoWest conference in Gothenburg, Sweden, Mandapati explained how easy it was to migrate.

“If you’ve already built your app with OpenAI, migrating to other models is simple… it only takes us minutes,” Mandapati said in an interview.

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DeepSeek’s entry into the AI landscape is having a significant impact, particularly on pricing models. Interviews with startup leaders and investors reveal that the company’s affordable pricing structure is forcing competitors to reconsider their pricing and improve their models. According to Mandapati, DeepSeek’s pricing is five times lower than what competitors offer.

“DeepSeek offered pricing that was five times cheaper than competitors,” Mandapati explained. “I’m saving a lot of money, and users won’t notice any difference.”

European startups have long faced challenges in keeping pace with their American counterparts, primarily due to easier access to funding and resources. However, with DeepSeek’s cost-effective technology, European companies now have a chance to close the gap.

“This is a huge step toward democratizing AI and leveling the playing field with major tech giants,” said Seena Rejal, CEO of Netmind.AI, a UK-based company and one of DeepSeek’s early users.

Research from Bernstein analysts shows that DeepSeek’s pricing is 20 to 40 times lower than OpenAI’s. For example, OpenAI charges $2.50 for every $1 million in input tokens, while DeepSeek charges just 0.014 dollars for the same amount.

Despite the promising advantages, there are regulatory concerns. DeepSeek is under investigation in several European countries to determine whether it has copied data from OpenAI or if it is censoring responses to avoid negative portrayals of China.

A Shift In The AI Market

In 2024, the U.S. saw nearly $100 billion in venture capital investments in AI companies, while Europe only managed $15.8 billion, according to PitchBook data. Meanwhile, U.S. President Donald Trump recently unveiled Stargate, a $500 billion joint venture between OpenAI, SoftBank, and Oracle.

In Europe, investments in AI remain modest. However, some companies, like France’s Mistral, are managing to compete with the major players such as OpenAI, Meta, and Google. DeepSeek caught attention after it was revealed that the cost of training its DeepSeek-V3 model was less than $6 million using NVIDIA H800 computing power, making it one of the most affordable AI models to date.

“This shows that bigger isn’t always better,” said Fabrizio del Maffeo, CEO of Axelera AI. “As AI models become more accessible, costs fall, and barriers to innovation decrease, accelerating industry development.”

While some analysts question whether DeepSeek’s training costs are as low as reported, there’s no doubt that they are significantly cheaper than their U.S. counterparts. Ulrik R-T, CEO of Empatik AI, a Danish startup, sees DeepSeek as an opportunity for companies without large budgets.

“It proves we don’t need enormous budgets to realize our vision,” R-T said.

The Price War Begins

The shift in pricing has already triggered changes in the industry. Recently, Microsoft announced it would offer its OpenAI-powered logical reasoning model for free to Copilot users, a departure from its usual $20 per month subscription fee.

“AI prices are falling, so future solutions are likely to focus on more transparent, open-source models—even if they come from China,” said Joachim Schelde of Scale Capital.

However, larger corporations like Nokia and SAP are more cautious about these developments. According to Alexandru Voica, head of the corporate department at Synthesia, a UK-based company valued at $2.1 billion, price is just one factor.

“Other considerations include security certifications and software ecosystems that allow companies to integrate AI solutions into their platforms,” Voica added.

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AI Spending Is Complicating The Fed’s Fight Against Inflation

by News Editor

August 12, 2026

Silicon Valley leaders have long argued that artificial intelligence will make technology and services dramatically cheaper. OpenAI CEO Sam Altman has described a future where intelligence becomes extremely inexpensive, while Tesla and SpaceX CEO Elon Musk has predicted that AI and robotics will create greater abundance and drive down costs.

So far, those benefits have yet to materialise at scale. AI adoption remains relatively slow, while the enormous investment needed for data centres and AI infrastructure is putting pressure on electricity prices, supply chains and other costs. For the Federal Reserve, this creates a difficult balancing act: AI could eventually boost productivity and reduce inflation, but its current buildout is contributing to higher prices.

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OpenAI chief economist Ronnie Chatterji said AI needs to be adopted by organisations and generate measurable value before its broader economic impact becomes visible in productivity statistics.

AI Adoption Remains Uneven

Capital spending on AI infrastructure in the U.S. is expected to reach $581 billion this year, according to Goldman Sachs Research, with global investment potentially reaching $1 trillion.

Despite the scale of spending, adoption remains far from universal. A May survey by the U.S. Census Bureau found that 17% to 20% of U.S. businesses reported using AI, with adoption significantly higher among large companies.

Companies that have implemented AI at scale also highlight the challenges. Julie Averill, former CIO of Lululemon, said successful deployment requires changes in employee behaviour and trust in the technology. OpenAI has observed a similar divide: its most advanced business users deploy AI at around eight times the rate of average companies.

Why Productivity Gains May Take Time

Economists point to the limits of automation. AI can perform individual tasks effectively, but many jobs combine tasks that are difficult to automate.

Stanford professor Charles Jones refers to these as “weak links”. Radiology, for example, involves interpreting scans but also communicating with patients and working with colleagues. AI can automate part of the job without eliminating the profession itself.

As a result, the full economic impact of AI may not become clear until businesses adopt the technology more broadly and reorganise their operations around it.

AI Adds To The Fed’s Policy Challenge

AI’s economic impact has become part of the Federal Reserve’s policy debate. Fed Chairman Kevin Warsh has argued that AI could eventually become a significant disinflationary force by increasing productivity and strengthening U.S. competitiveness.

Other officials are more cautious. In July, the Fed kept interest rates at 3.5% to 3.75%, while some officials expressed concern that AI infrastructure spending could add to inflationary pressures.

Minneapolis Fed President Neel Kashkari pointed to massive data-centre investment as a new source of demand. Household electricity prices rose 10% in the two years through July, compared with a 6.2% increase in overall consumer prices. Meanwhile, shortages of chips and other AI components are pushing up costs. JPMorgan Chase estimates that DRAM prices could rise 400% by the end of 2026 compared with 2024.

Warsh has consequently adopted a more cautious tone, saying that while AI investment is laying the groundwork for future growth, the timing and scale of its economic effects remain difficult to predict.

For the Fed, the challenge is clear: AI could eventually deliver major productivity gains, but the cost of building that future is already showing up in the economy.