Teradata report shows general AI deployment pressure

teradata report shows general ai deployment pressure

According to a survey conducted jointly by IDC and Teradata, it’s intriguing to note that only 30% of companies seem to be fully prepared for the advent of generative AI. The survey, backed by Teradata, sheds light on an interesting dynamic: while there’s substantial pressure from top management for companies to embrace generative AI, the actual readiness on the ground appears to be at a modest 30%.

This comprehensive survey engaged 900 C-Suite executives from various corners of the globe. An eye-catching statistic emerges: a staggering 90% of these high-level executives do comprehend the potential that generative AI, often referred to as GenAI, holds. Despite this understanding, a significant majority – about two-thirds – of these executives do harbor concerns about the implications of diving into the GenAI realm. Specifically, they express reservations about potential biases and misinformation that might arise.

As the GenAI landscape evolves rapidly, with innovations like ChatGPT coming into play, the issue of bias becomes a focal point, garnering more attention than ever. What’s striking is that 85% of the survey respondents share that they’ve seen only marginal changes in this area, and they’re apprehensive that even greater challenges might lie ahead in the near future.

To adopt GenAI – Large enterprises face global pressure

Amidst the global landscape, it’s apparent that significant pressure is being exerted on large enterprises to embrace the wave of GenAI. The survey at hand illuminates an intriguing transformation: a considerable 54% of these enterprises claim that information within their organizational framework is flowing unhindered, showcasing their journey towards digital maturity.

Still, the executives steering these large enterprises across the world are confronting formidable pressures to incorporate GenAI into their operations. This push is driven by the escalating complexity of data and the pressing need to bridge the expanding skills gap within the industry.

Intriguingly, despite the fact that almost 80% of the 900 global executives polled have high or substantial trust in the potential of AI to enhance their company’s future endeavors, the survey underscores that more groundwork remains to be covered.

Further insights from the survey unveil the extent to which these executives have experienced substantial corporate transformations in the past two years. A significant number of participants observed shifts in focus towards economic challenges and corresponding changes, a surge in remote and hybrid work patterns, and an amplified emphasis on environmental, social, and governance (ESG) considerations.

Parallel to these shifts, there exists a considerable skills gap in the realm of GenAI. Mere 30% of the surveyed executives express preparedness to harness GenAI’s capabilities today. A slightly higher 42% harbor confidence that they will be fully equipped with the necessary skills to implement GenAI within the next 6 to 12 months.

Curiously, an impressive 89% of these individuals claim to grasp the potentials and merits of GenAI, yet an intriguing 57% hold the belief that interest in GenAI products might wane over time.

Businesses easily catch up with the trend of digital transformation

In an exclusive conversation with AI Magazine, Hillary Ashton, the Chief Product Officer at Teradata, delved deeper into corporations’ perceptions of AI’s potential in the near future.

According to her, “Generative AI and large language models (LLMs) are on the verge of revolutionizing every industry. While there’s immense excitement surrounding Gen AI and LLMs, it’s essential for businesses to remain grounded and not be overly captivated by their novelty.”

“Companies should be wary of squandering resources without a clear business value. My suggestion is to start with a well-defined end goal, consistently assess ROI, and weigh it against price performance.”

As part of staying ahead in the realm of digital transformation, Ashton emphasized the significance of identifying meaningful use cases and their associated benefits, including enhancing customer experience.

She emphasized, “Solid data serves as the cornerstone for successful digital transformation and AI implementation. Businesses must invest in technologies that enhance data quality, governance, and reliability.”

“A cloud analytics platform that integrates data from diverse sources and structures across the business is pivotal. Enabling all business facets to access synchronized data and self-service solutions accelerates the value extraction from data and expedites the deployment of AI/ML projects.”

Speaking about AI’s role in the cybersecurity arena, she noted, “AI has the potential to address the cyber skills gap effectively. However, this relies on trusting AI to provide accurate and ethical outcomes.”

“Data indicates a notable trust gap in AI implementation. The initial step to bolster trust and confidence in AI involves commencing with clean, dependable data.”

Addressing the impact of hybrid work models on AI’s perception, Ashton commented, “AI’s reliability is contingent on both users and implementation processes. With more people working remotely or in various settings, it’s crucial for all teams to use a platform that harmonizes enterprise data, ensuring data governance, integrity, and model management.”

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