According to an IDC white paper, companies achieving faster “decision velocity” through AI share common attributes such as clear goals, active technology investment, and pragmatic use of AI, analytics, and data technologies. These organizations are achieving greater decision velocity in a volatile and complex environment. The paper cites a consumer packaged goods company as an example of AI-powered decision intelligence in practice. IDC’s research emphasizes the value of decision intelligence in enterprise digital transformation and the need for innovative technology to accelerate accurate decision-making at scale.
Despite the increasing pressure for companies to implement AI strategies, a survey conducted by Ciscoreveals that the majority of business leaders lack the necessary infrastructure, policies, talent, culture, and data to do so. While 97% of respondents acknowledge the urgency to use AI technology, only 14% are fully prepared for the transition. The survey highlights the gap between companies’ AI ambitions and operational realities, particularly regarding data readiness and governance. It emphasizes the importance of effective governance, training, and change management to address these challenges and ensure successful AI implementation.
According to Snow Software’s IT Priorities survey, IT leaders’ top priorities are integrating AI, security risk mitigation, and IT cost reduction. Budget concerns are prevalent across tech categories, with overspending reported in cloud services, security tools, hardware, on-prem software, and SaaS applications. IT leaders recognize the need for better visibility into spending and usage, especially as organizations adopt generative AI tools and push for innovation.
A study by SnapLogic has found that generative AI can save office workers a significant amount of time, with nearly half of the respondents confident that it could save them a day’s work per week. However, many workers lack understanding of gen-AI, and a significant percentage have not received adequate training to use it effectively. Despite this, employees desire to learn more about gen-AI, as they believe it is vital for career advancement. Employers should be aware that some workers are using gen-AI without disclosing it, highlighting the need for staff training and clear guidance.
Why do we care?
These studies point to transforming services where AI is central to business strategies. The challenges of readiness, governance, cost management, and employee training are critical areas where IT service providers can offer valuable solutions and support. Clear objectives, consistent technology investment, and practical application of AI and data analytics mark companies who succeed.
Most businesses recognize the urgent need for AI but lack the infrastructure, policies, talent, and data governance to implement it effectively. This gap points to a significant opportunity for IT service providers to offer data readiness, governance, and AI-focused training and change management solutions.