As artificial intelligence (AI) continues to grow in prominence, organizations are facing significant challenges in overcoming skills gaps and outdated infrastructure to fully harness its potential. A recent survey conducted by Cloudera, a hybrid platform for data, analytics, and AI, revealed that while 88 percent of enterprises are adopting AI in some capacity, many are struggling to leverage it effectively due to insufficient data infrastructure and a lack of skilled employees.
The State of Enterprise AI and Modern Data Architecture survey, which included input from 600 IT leaders across the U.S., EMEA, and APAC regions, highlighted the barriers that exist for enterprise AI adoption on a global scale. These barriers range from concerns about security and compliance risks associated with AI (74 percent) to the absence of proper training or talent to manage AI tools (38 percent), and the perceived costliness of AI tools (26 percent). These findings underscore the need for organizations to address key pillars of a resilient AI strategy that are currently being overlooked.
Despite the rapid adoption of AI across industries, the survey also shed light on the critical role of education in preparing future generations for the workforce. With AI becoming a ubiquitous presence in business operations, decision-making processes, innovation, and customer experiences, it is imperative for educational institutions to equip students with the necessary AI skills to thrive in a competitive job market.
Recognizing this need, a new commission comprising policymakers, education leaders, business executives, and other stakeholders from 16 states is focusing on AI’s role in education from kindergarten through postsecondary programs. Chaired by South Carolina Governor Henry McMaster and co-chaired by Brad D. Smith, president of Marshall University and former CEO of Intuit, the Southern Regional Education Board (SREB) Commission on Artificial Intelligence in Education aims to develop recommendations for using AI in teaching and learning, shaping AI-related policies, and preparing students for AI careers.
One of the key takeaways from the survey is the critical importance of trustworthy data in all AI endeavors. While 94 percent of respondents expressed trust in their data, over half of them indicated a preference for a root canal over attempting to access all of their company’s data. This frustration stems from challenges such as contradictory datasets, governance issues across platforms, and data overload. These challenges underscore the necessity of implementing a modern data architecture that enables seamless access to data across the organization in a secure and reliable manner.
The survey also highlighted the top use cases for AI, including enhancing customer experiences, improving operational efficiency, and expediting analytics. Companies are leveraging AI technology to bolster security and fraud detection, automate customer support processes, offer predictive customer service, and power chatbots to enhance customer interactions. Moreover, AI is being integrated across various business functions beyond IT, with applications in customer service, marketing, and analytics to drive informed decision-making and gain a competitive edge.
As organizations strive to adopt AI more effectively, the quality of data and its management emerge as critical factors for success. Cloudera’s Chief Strategy Officer, Abhas Ricky, emphasized the importance of managing data where it resides to enable cost-efficient AI model deployment. By bringing AI models to the data instead of vice versa, enterprises can leverage the advantages of utilizing data effectively and running models efficiently.
In conclusion, the journey towards enhanced AI implementation requires a concerted effort to bridge skills gaps, modernize data infrastructure, and prioritize AI education. By addressing these challenges head-on and leveraging AI’s transformative potential, organizations can unlock new opportunities for growth, innovation, and success in the digital age.
