AI isn’t just changing how Web3 companies build – it’s redefining how they work
Artificial intelligence is no longer a separate tool or a side experiment for Web3 companies. It’s becoming the backbone of how teams work, learn, automate, and make decisions.
Across the industry, AI is being integrated not only into products, but into internal operations – from code review and research to marketing, analytics, and people processes.
This shift is also visible inside WhiteBIT, where AI is gradually becoming part of everyday work. At WhiteBIT – a crypto exchange where innovation isn’t just a buzzword, but a core value, AI is not an isolated initiative. It’s integrated into the company’s operating rhythm. Teams run regular AI trainings, collaborate with external experts, explore advanced models, and share their best practices across departments.
Employees work with paid versions of ChatGPT, Gemini Pro, and other advanced models to automate research, structure complex tasks, enhance decision-making, and accelerate product cycles. Alongside this, different teams actively test a wide range of AI tools – from presentation tools like Beautiful AI and Gamma, to branding and design generators such as Looka, idea-visualization apps like Napkin, and transcription or localization assistants such as Turboscribe and Rask. These experiments help teams ideate, visualize, document, and deliver outcomes faster.
Why This Matters for Talent
For talent, this shift is meaningful. It reflects a workplace where modern tooling is the norm, where teams experiment openly, and where people are encouraged to build smarter rather than work harder.
In a fast-moving space like Web3, specialists want an environment that supports curiosity, removes friction, and gives them leverage – not limitations. And AI at WhiteBIT does exactly that: it amplifies expertise, shortens learning curves, and lets people focus on the work that actually moves the product forward.
And recruitment is one of the first areas where this transformation becomes visible – shaping not only how a company evaluates talent, but how talent evaluates a company.
Web3 Is Outpacing Traditional Hiring
According to a16z’s State of Crypto report, the web3 industry is scaling faster than nearly any other tech sector, and the talent gap grows every year. Traditional HR tools can’t keep up with decentralized, open-source-first, high-velocity environments.
AI fills this gap. It automates what slows companies down and amplifies what makes Web3 teams effective: ownership, transparency, and speed.
Why Talent Evaluation Needs a New Lens
AI is reshaping how Web3 companies hire, giving teams a clearer and more objective view of a candidate’s strengths. Tools like HireEZ, Ashby AI, Codeium, Sourcegraph AI, Eightfold, Pymetrics, and assistants such as ChatGPT or Gemini reveal signals that résumés can’t capture: how someone thinks, adapts, learns, and communicates.
It also strengthens the hiring system itself – reducing manual work, improving consistency, and speeding up decisions. Research from Gartner (2025) and Deloitte Human Capital shows the same trend: AI-supported hiring increases precision, fairness, and the time teams can dedicate to meaningful recruiter–candidate interaction.
The result is a more human process focused on motivation, mindset, and long-term fit.
Case Study: AI in Web3 Recruitment
As part of its talent strategy, WhiteBIT partnered with mypitch – an AI-driven evaluation platform – to support early-stage screening.
While AI handles analytical pre-assessment, recruiters focus on motivation, culture fit, communication, and vision alignment. This hybrid model keeps hiring standards extremely high while maintaining speed – a critical advantage in the competitive Web3 talent market.Beyond analytical pre-assessment, AI also gives recruiters early context that text CVs can’t provide. It highlights how candidates communicate and present their motivation, then summarizes these signals to help teams focus on the most relevant profiles. All shared information remains consent-based, keeping the process transparent and respectful for candidates.
Innovation by Design: The New Standard for Employers
For candidates, this shift speaks volumes. It shows a workplace where AI accelerates real work, where experimentation is normal, and where teams grow together through open knowledge sharing.
Companies like WhiteBIT are setting the new global benchmark for the future of work, proving that in Web3, technology isn’t just a product; it’s the architecture of company culture.
And for talent looking for a place where AI enhances their impact – not replaces it – this blend of technology, autonomy, and ambition becomes a reason to take a closer look. And this is only the beginning. As AI evolves, the way teams learn, collaborate, and grow will evolve with it.
If you want to join the WhiteBIT team please check vacancies here.
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Building the Next-Gen Workplace: How AI Is Redefining Web3 Companies for Talent
AI isn’t just changing how Web3 companies build – it’s redefining how they work
Artificial intelligence is no longer a separate tool or a side experiment for Web3 companies. It’s becoming the backbone of how teams work, learn, automate, and make decisions.
Across the industry, AI is being integrated not only into products, but into internal operations – from code review and research to marketing, analytics, and people processes.
This shift is also visible inside WhiteBIT, where AI is gradually becoming part of everyday work. At WhiteBIT – a crypto exchange where innovation isn’t just a buzzword, but a core value, AI is not an isolated initiative. It’s integrated into the company’s operating rhythm. Teams run regular AI trainings, collaborate with external experts, explore advanced models, and share their best practices across departments.
Employees work with paid versions of ChatGPT, Gemini Pro, and other advanced models to automate research, structure complex tasks, enhance decision-making, and accelerate product cycles. Alongside this, different teams actively test a wide range of AI tools – from presentation tools like Beautiful AI and Gamma, to branding and design generators such as Looka, idea-visualization apps like Napkin, and transcription or localization assistants such as Turboscribe and Rask. These experiments help teams ideate, visualize, document, and deliver outcomes faster.
Why This Matters for Talent
For talent, this shift is meaningful. It reflects a workplace where modern tooling is the norm, where teams experiment openly, and where people are encouraged to build smarter rather than work harder.
In a fast-moving space like Web3, specialists want an environment that supports curiosity, removes friction, and gives them leverage – not limitations. And AI at WhiteBIT does exactly that: it amplifies expertise, shortens learning curves, and lets people focus on the work that actually moves the product forward.
And recruitment is one of the first areas where this transformation becomes visible – shaping not only how a company evaluates talent, but how talent evaluates a company.
Web3 Is Outpacing Traditional Hiring
According to a16z’s State of Crypto report, the web3 industry is scaling faster than nearly any other tech sector, and the talent gap grows every year. Traditional HR tools can’t keep up with decentralized, open-source-first, high-velocity environments.
AI fills this gap. It automates what slows companies down and amplifies what makes Web3 teams effective: ownership, transparency, and speed.
Why Talent Evaluation Needs a New Lens
AI is reshaping how Web3 companies hire, giving teams a clearer and more objective view of a candidate’s strengths. Tools like HireEZ, Ashby AI, Codeium, Sourcegraph AI, Eightfold, Pymetrics, and assistants such as ChatGPT or Gemini reveal signals that résumés can’t capture: how someone thinks, adapts, learns, and communicates.
It also strengthens the hiring system itself – reducing manual work, improving consistency, and speeding up decisions. Research from Gartner (2025) and Deloitte Human Capital shows the same trend: AI-supported hiring increases precision, fairness, and the time teams can dedicate to meaningful recruiter–candidate interaction.
The result is a more human process focused on motivation, mindset, and long-term fit.
Case Study: AI in Web3 Recruitment
As part of its talent strategy, WhiteBIT partnered with mypitch – an AI-driven evaluation platform – to support early-stage screening.
While AI handles analytical pre-assessment, recruiters focus on motivation, culture fit, communication, and vision alignment. This hybrid model keeps hiring standards extremely high while maintaining speed – a critical advantage in the competitive Web3 talent market.Beyond analytical pre-assessment, AI also gives recruiters early context that text CVs can’t provide. It highlights how candidates communicate and present their motivation, then summarizes these signals to help teams focus on the most relevant profiles. All shared information remains consent-based, keeping the process transparent and respectful for candidates.
Innovation by Design: The New Standard for Employers
For candidates, this shift speaks volumes. It shows a workplace where AI accelerates real work, where experimentation is normal, and where teams grow together through open knowledge sharing.
Companies like WhiteBIT are setting the new global benchmark for the future of work, proving that in Web3, technology isn’t just a product; it’s the architecture of company culture.
And for talent looking for a place where AI enhances their impact – not replaces it – this blend of technology, autonomy, and ambition becomes a reason to take a closer look. And this is only the beginning. As AI evolves, the way teams learn, collaborate, and grow will evolve with it.
If you want to join the WhiteBIT team please check vacancies here.