After witnessing the influence of ChatGPT’s accomplishments on AI strategies within businesses, 2023 is poised to be a pivotal year for the extensive acceptance of this technology. Companies are actively working to incorporate general AI into various facets of their operations in preparation for the upcoming year, 2024.
Despite this progress, a recent survey carried out by Forrester Consulting among 220 AI decision-makers in North American companies has shed light on persistent concerns and obstacles that are obstructing the seamless integration of AI technologies.
The survey has brought to the forefront significant challenges, including worries about potential risks such as hallucinations, which are acting as barriers to the implementation of foundational AI models for planned use cases, thereby keeping numerous organizations in the exploration phase.
Acknowledgment of the Revolutionary Impact of General AI
Businesses spanning diverse industries are increasingly acknowledging the revolutionary impact of relational AI, driven by numerous success stories circulating online.
As per the Forrester study commissioned by Dataiku, 83% of the participants have initiated the exploration or experimentation with collaborative AI (colAI).
Furthermore, just over 60% of the respondents consider AI to be critical or extremely vital for their business strategies, with intentions to increase investments in data/AI initiatives by up to 10% in the coming year.
These insights signify a proactive approach towards AI adoption, with a majority of the participants recognizing multiple potential applications, including knowledge management (56%), self-service data analytics (59%), and product development (64%).
The survey reflects a sense of curiosity and eagerness among companies to embrace the diverse transformative capabilities of AI in the foreseeable future. Anticipated advantages include enhancing existing offerings, creating new products and services, and streamlining internal and external processes.
Ongoing Hurdles in AI Implementation
Despite the optimistic outlook, industry leaders have outlined various challenges hindering the adoption of general AI. Concerns range from the potential breach of data protection laws (31%) to the complexities associated with acquiring the requisite skills and governance structures to effectively oversee AI technologies.
More than half of the respondents have raised concerns about the potential biases and hallucinations that could compromise the quality of AI outcomes. Inadequacies in infrastructure further amplify these risks, with the absence of robust data systems identified as the primary hurdle.
A notable portion (35%) of the participants have pointed out inadequate infrastructure for managing vast volumes of data, while others have highlighted integration challenges with existing systems and mathematical limitations.
Governance mechanisms (35%), interpretability and explainability of AI (25%), talent shortages (31%), and scalability issues with AI models have also been identified as significant obstacles.
To tackle these challenges, organizations are advised to embrace a strategy that offers integrated capabilities through AI platforms. These platforms provide pre-packaged solutions for swift development, a structured environment for seamless integration, robust frameworks, and security features to ensure compliance and standardization.
According to McKinsey, generative AI has the potential to enhance annual corporate profits by \(2.6 trillion to \)4.4 trillion, with substantial impacts anticipated in the banking, high-tech, and life sciences sectors.
