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AI Essential To Success For 93% Large Companies, But 76% Face Talent Shortage: Research

AI enablement continues to be important for large businesses, with 54% using and integrating AI throughout their organisations.

<div class="paragraphs"><p>Artificial intelligence - AI (Source: rawpixel.com/Freepik)</p></div>
Artificial intelligence - AI (Source: rawpixel.com/Freepik)

New research commissioned by UST, a digital solutions company, has found that most organisations are on board the artificial intelligence wagon but lack a skilled AI workforce. Obstacles to implementation include a lack of in-house AI skills, complex regulatory requirements and rising ethical concerns. These factors create uncertainty, slowing AI implementation and preventing the technology from reaching its full potential.

According to the research, 76% of respondents cited a shortage of AI-skilled personnel. While 92% agreed that AI implementation aligns with their strategic goals, only 5% reported no significant challenges in deployment. Fewer than 40% of organisations have confidence in their responsible AI framework, and around 70% are concerned that a lack of diversity in their AI workforce leads to biased outcomes.

Clear Management Buy-In

AI enablement continues to be important for large businesses, with 54% using and integrating AI throughout their organisations, 28% using it throughout the business but in an unstructured way, and 16% starting to experiment with AI. Only 1% do not use AI and they have no plans to do so.

Significantly, 92% respondents said their company’s AI implementation aligns with their strategic goals, and 93% believe AI will be essential to success in the next five years. However, only 8% said they do not face barriers to these goals. Most organisations encounter substantial obstacles that hinder AI implementation. Also, 89% said their organisation needs to increase spending on AI implementation to keep up with its competitors.

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Roadblocks Remain

Of the respondents, 44% described the AI implementation process as challenging, citing security concerns (40%), shortage of in-house expertise (33%), and compliance and regulatory challenges (33%) as top issues. The lowest-ranking barrier was "no clear understanding of the benefits" (14%), showing that there is clear consensus on the value of AI.

Over three-quarters (76%) said there is a severe shortage of AI-skilled personnel in their organisation. Almost nine in 10 (89%) said their organisation needs external guidance on implementing AI effectively, with 57% planning to engage with external third-party AI expertise in the next three years.

Furthermore, 67% believe there are insufficient external advisors focusing on AI implementation, and 38% consider external expertise less expensive than in-house. Also, 31% of respondents cannot upskill their own workforce.

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Lack Of AI Framework

Around 91% agreed their organisation must have a responsible AI framework/policy. However, 39% consider their current approach "very effective". Respondents believe more regulation is required for successful and responsible AI implementation in their industry (91%) and in companies across all industries (92%). The main reasons for this regulation should be to ensure data privacy (62%), better transparency (57%) and ethical usage (55%).

Regarding their AI workforce, 80% said diversity is crucial or very important. However, 32% believe their AI team is lacking diversity, and 70% are concerned that this leads to biased outcomes. 

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AI Spending And ROI

Around 5% of respondents currently spend more than half of their technology budget on AI implementation, but 18% predict they will spend at this level within three years. On an average, organisations expect to see a return on investment in AI technology in approximately two years. However, 23% expect this to take four or more years.

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ESG Benefits Of AI

Almost nine in 10 respondents believe AI can help their organisation work towards their net-zero goals, and 91% said that AI has significant ESG benefits. Respondents believe AI improves sustainability measurements and reporting (68%), reduces carbon emissions/accelerates efforts to reach net zero (58%) and reduces resource consumption (55%).

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