While the promise of these predictions may yet come to fruition, companies are currently grappling with significant obstacles as they attempt to scale their AI initiatives from pilot projects to widespread adoption across their enterprises. Only about 5.4% of US companies were leveraging AI to deliver goods and services by 2024.
As organizations move beyond tentative explorations of AI adoption, similar to incremental advancements in coding technologies and customer service, a more comprehensive approach emerges, requiring deliberate transformations in infrastructure, knowledge management, and partner networks to achieve widespread integration. As a matter of course, organizations must carefully consider the potential uncertainties surrounding advancements in AI performance and develop strategies for evaluating the return on investment.
As organisations prepare to scale AI across the enterprise in the years ahead, it’s crucial to act now.
This comprehensive report provides insights into the current state of enterprise AI adoption, offering a practical guide on how business leaders can turn their aspirations into tangible results by developing effective AI strategies. Key findings embrace the next:
Nearly all companies – a staggering 95% – have already adopted AI technology, while an overwhelming 99% expect to do so in the future. Although many organizations have successfully launched AI pilots, just 24% have been able to scale these initiatives beyond a handful of uses. As the majority of companies prepare to fully integrate AI across their entire operations within the next two years, this critical year sets the stage for laying the groundwork for enterprise-wide adoption.
Total AI spending in 2022 and 2023 remained stable for most companies, with only a quarter of them increasing their investment by more than a quarter. By 2024, the trend is expected to shift, with nearly nine out of every ten respondents projecting increased investment in AI spending for knowledge readiness, platform modernization, cloud migration, and knowledge quality, as well as adjacent areas such as technology, cultural transformation, and business models. Four in every ten consumers expect to increase their spending by 10% to 24%, while roughly a third of respondents predict an expansion of up to 49%.
The ability to effortlessly integrate, combine, and scrutinize information from a wide range of sources empowers organizations to identify relevant insights and effectively apply them to specific business scenarios. By leveraging pre-curated content, this tool eliminates the need to search through extensive databases, providing users with a streamlined experience where relevant information is readily available and tailored to their specific objectives.
Almost half of those surveyed pinpointed limited knowledge quality as the primary hindrance to effective knowledge deployment. While particularly relevant to larger organizations with existing IT frameworks and significant investments in legacy systems. Large corporations with revenues exceeding US$10 billion are more likely to identify high-quality knowledge and infrastructure limitations, implying that organisations overseeing vast knowledge repositories face significantly greater challenges in addressing these issues.
Ninety-eight percent of organizations claim they are willing to sacrifice being the first to adopt AI if it means ensuring a safe and secure deployment. Governance, safety, and privacy concerns are the primary brakes on the pace of AI adoption, according to 45% of respondents, with 65% of executives at major companies sharing this sentiment.
