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    Home»Business»AI adoption surges among small businesses, 40% plan to add new jobs
    Business

    AI adoption surges among small businesses, 40% plan to add new jobs

    Justin M. LarsonBy Justin M. LarsonAugust 8, 2025No Comments4 Mins Read
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    Goldman Sachs global head of corporate engagement Asahi Pompey unpacks AI ambitions across America on ‘The Claman Countdown.’

    Small business owners are rapidly adopting artificial intelligence to power their growth, with many saying it will lead to more job opportunities this year, according to a Goldman Sachs survey.

    About 68% of small business owners say they are already using AI, with another 9% planning to begin using it within the next year, according to new data from Goldman’s 10,000 Small Businesses Voices survey. 

    It’s a significant jump from the 51% of small business owners who were using the technology to increase productivity and expand their capabilities two years ago. 

    Most small businesses, about 80%, said AI is enhancing rather than replacing their workforce. About 74% of small business owners using AI plan to grow their business in 2025. That compares to 65% of those not using AI or unsure about adoption. Nearly 40% of small businesses say the technology will allow them to create new jobs in 2025. 

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    This comes as public anxiety grows over whether AI will replace jobs. According to a 2025 Pew Research Center survey, more than 60% of Americans believe AI will result in fewer jobs over the next 20 years. 

    However, about 80% of the small businesses that have already adopted the technology say it increased the efficiency and productivity of the company. Over 50% say they have been given better data for decision-making, with another 49% saying it helped offer new capabilities, according to the survey.

    OpenAI logo

    The OpenAI logo is displayed on a mobile phone screen. (Beata Zawrzel/NurPhoto via Getty Images / Getty Images)

    Still, despite the rapid adoption, about 42% of small businesses say they still don’t have access to the resources and expertise necessary to successfully deploy it. Of those businesses, 60% cite a lack of expertise in applying AI to their business. However, 42% say it’s not relevant to their business model, highlighting an information and resource gap. 

    Those who have adopted technology for their business have still confronted challenges, with 48% saying they are struggling to choose the right tools, 46% express concerns about data privacy and security, and 41% cite a lack of technical expertise.

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    Workday posted a blog earlier this year, highlighting how AI is becoming the standard for modern small businesses, and that AI is critical to helping small businesses create efficient workforce management to stay productive without overburdening staff. 

    ChatGPT, Gemini and Claude shown on a phone screen

    AI assistant apps on a smartphone – OpenAI ChatGPT, Google Gemini and Anthropic Claude. (Getty Images / Getty Images)

    “Cutting-edge technologies such as artificial intelligence (AI) and machine learning once seemed like a luxury for large enterprises—but today, they’re becoming the competitive standard for businesses of every size and industry,” Workday said in an April blog. 

    For small businesses in particular, “artificial intelligence is leveling the playing field with larger organizations, offering new levels of scalability and productivity that may have once felt unattainable,” Workday added. 

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    Still, accounting giant E&Y said this transformation will bring about massive structural change and disruption to existing business and operating models, emphasizing the importance of regulation. 

    xAI-Grok

    The xAI and Grok logos are seen in this illustration photo. (Photo by Jaap Arriens/NurPhoto via Getty Images / Getty Images)

    The company said that a successful organization will have robust risk assessment and validation processes; clear frameworks for human oversight of AI systems; strong stakeholder communication and trust-building capabilities; flexible operational models that can adapt to evolving AI regulations; balanced automation strategies that prioritize reliability over speed; and a comprehensive understanding of their internal and external value chains, along with the AI systems driving them.



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