AiThority 2024年09月13日
Nearly 70 Percent of Leaders Prioritize GenAI for Data, with Almost Half Expecting to Double ROI in Three Years, Study Reveals
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一项由MIT SMR Connections与ThoughtSpot联合发布的研究表明,生成式AI在分析领域正被越来越多的企业采用,早期采用者已经看到了显著的竞争优势,并预计将在未来几年内获得更高的投资回报率。研究显示,早期采用者通过生成式AI加速了数据驱动决策,提升了产品和服务质量,并改善了商业洞察的质量。

🚀 **生成式AI加速数据驱动决策:** 早期采用者发现生成式AI能够显著加快数据驱动决策,帮助企业领导者快速分析复杂数据集、预测趋势,并模拟各种情景,从而更准确地预测和应对市场变化。这项技术已使超过三分之一的早期采用者在竞争中脱颖而出。

🤝 **协作与人才至关重要:** 生成式AI的成功实施取决于关键因素,包括不断发展技能、培养业务和数据团队之间的强有力合作,以及选择合适的工具来支持业务战略。成功的早期采用者普遍建立了清晰一致的沟通机制,确保业务和数据团队之间达成一致的执行策略,从而建立了强大的合作关系。

🧰 **选择合适的工具和人才:** 研究发现,成功的早期采用者更倾向于利用第三方生成式AI工具,并与外部专家合作,优化资源,减少内部团队的投入,从而加速部署和扩展。此外,他们还认识到自然语言处理(NLP)的重要性,并优先考虑培养相关人才,以充分发挥生成式AI的潜力。

👀 **人类在环路中的重要性:** 虽然生成式AI能够提供强大的分析能力,但人类在环路中仍然至关重要,需要对AI生成的输出进行监控和调整,以确保其准确性和可靠性。人类的介入可以纠正AI的错误,避免潜在的偏差,并提高AI模型的准确性,从而建立信任并促进AI的有效应用。

📈 **投资回报率的显著提升:** 随着早期采用者不断扩大部署规模,他们预计与仍在计划阶段的企业之间的竞争差距将进一步扩大。超过三分之一的早期采用者预计将在未来三年内实现大幅收入增长,其中近一半预计投资回报率(ROI)将达到100%,甚至超过10%的企业预计ROI将超过300%。这些发现凸显了生成式AI在分析领域的重要性和其带来前所未有的商业价值的潜力。

New research by MIT SMR Connections, sponsored by ThoughtSpot, highlights the imperative of adopting generative AI for analytics, with 37% of early adopters viewing their generative AI use putting them far ahead of market and competitors

A new MIT SMR Connections report sponsored by ThoughtSpot, the AI-Powered Analytics company, explores how early adopters of generative AI for analytics are gaining a significant competitive edge, with many already experiencing positive results, and a majority seeing significant returns from their investments.

The report drew responses from 1,000 business and data leaders in multiple industry sectors across North America, Europe, and Asia-Pacific. Of the 1,000 global respondents, 67% are already leveraging generative AI for an analytics use case, with 26% planning to, and 7% evaluating its use.

Also Read: AiThority Interview with Paul Fipps, President, Global Industries and Strategic Growth at ServiceNow

Early Adopters Set New Competitive Benchmarks

According to the report, the early adopters find that the technology’s ability to accelerate data-driven decision-making is a key benefit of implementation (44%), alongside its ability to improve products and services (44%), closely followed by how the technology can improve the quality of business insights (42%).

As the early adopters advance the number and scale of their deployments, they expect the competitive gap to widen between themselves and those only in planning mode. Over a third of early adopters (35%) project major revenue boosts, including almost half (48%) expecting a 100% return on investment (ROI) within three years, and over one in ten (12%) expecting their ROI to exceed 300% within the same period. The findings underscore the business imperative for generative AI in analytics, and the technology’s potential to deliver unprecedented business value.

The Impact on Business Decision-Making

Making swift, data-backed decisions is an important competitive advantage. It enables business leaders to quickly analyze complex datasets, forecast trends, and simulate scenarios, enhancing their ability to anticipate and plan for market changes with significant accuracy. According to the report, the implementation of generative AI for analytics has already placed over a third (37%) of early adopters far ahead of their competitors.

Also Read: AiThority Interview with Paul Fipps, President, Global Industries and Strategic Growth at ServiceNow

The Path to Generative AI Success in Analytics

The success of generative AI implementation hinges on key factors: evolving skill sets, fostering strong collaboration between business and data teams, and selecting the right tools to support business strategy.

To achieve this, organizations must establish clear and consistent communication between their business and data teams, ensuring alignment on a common execution strategy. The majority of early adopters (75%) report strong partnerships and a centralized strategy, putting them in an advantageous position. In contrast, less than half (47%) of planners – companies that haven’t yet adopted generative AI but expect to do so – have achieved similar alignment, underscoring the competitive edge that early adopters gain through prioritizing collaboration across the organization.

Both early adopters and planners recognize the importance of key technical skills for creating or customizing generative AI solutions, with data modeling cited as the most critical (49%) by all respondents. However, a notable difference emerges in their prioritization of natural language processing (NLP): many (41%) of the early adopters view NLP as a top priority, compared to just a limited share (28%) of planners. This divergence suggests that early adopters, having already deployed the technology, understand NLP’s potential to accelerate data-driven decision-making, positioning them to better attract and develop talent for effective use of generative AI.

The findings of the report also highlight the value of choosing the right tools and collaborating with external experts to enhance business outcomes. Over half (52%) of successful early adopters are leveraging third-party generative AI tools for analytics, compared with a smaller share (32%) of planners. By relying on strategic partnerships and external expertise, early adopters are optimizing their resources, while minimizing the time and effort required from their internal teams as they scale their deployments.

Finally, as generative AI is a new technology, experts interviewed in the report emphasize that it’s important to keep humans in the loop to monitor its output and make necessary changes. Having humans review AI-generated content provides opportunities to correct the technology’s mistakes and avoid problematic use cases or unintended biases. In turn, this helps train the models for accuracy, promotes trust, and enables humans to correct errors or misinterpretations closer to the source.

Thoughts from the Top

“For decades, data has been locked away in the hands of the expert analysts, and the wider industry has had a $100 billion price to pay for this annually. Now, the gap between those who are adopting generative AI for analytics and those who aren’t is stark,” said Cindi Howson, Chief Data Strategy Officer at ThoughtSpot. “With generative AI, organizations have the opportunity to deliver a data strategy more focused on business outcomes that delivers unprecedented value. Yet, success isn’t guaranteed. It’s a fast-evolving era, I encourage organizations to leverage lessons from early adopters that includes both technology and people considerations.”

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

The post Nearly 70 Percent of Leaders Prioritize GenAI for Data, with Almost Half Expecting to Double ROI in Three Years, Study Reveals appeared first on AiThority.

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生成式AI 分析 数据驱动决策 竞争优势 投资回报率
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