Ethical, Trust, and Skill Barriers Impede Generative AI Progress in EMEA
In the EMEA region, 76% of consumers anticipate significant impacts from AI in the next five years, yet 47% doubt its value, and 41% are concerned about its applications.
This insight comes from research conducted by enterprise analytics AI firm Alteryx.
Since OpenAI released ChatGPT in November 2022, the buzz around generative AI has highlighted its transformative potential, marking it as one of the most revolutionary technologies of our time.
Despite 79% of organizations reporting positive contributions from generative AI to their business, a gap remains in demonstrating AI’s value to consumers in both personal and professional contexts. According to the “Market Research: Attitudes and Adoption of Generative AI” report, which surveyed 690 IT business leaders and 1,100 members of the general public in EMEA, issues of trust, ethics, and skills are significant barriers to the successful deployment and broader acceptance of generative AI.
The Impact of Misinformation, Inaccuracies, and AI Hallucinations
AI hallucinations—where AI generates incorrect or illogical outputs—pose a major trust issue. Over a third of the public are anxious about AI’s potential to produce fake news (36%) and its misuse by hackers (42%). Additionally, half of the business leaders report dealing with misinformation generated by AI.
Concerns about the reliability of AI-generated information are widespread. Half of the general public reports inaccuracies in AI-produced data, and 38% find it outdated. Business leaders also worry about generative AI infringing on copyright or intellectual property rights (40%) and producing unintended outputs (36%).
A critical trust issue for businesses (62%) and the public (74%) revolves around AI hallucinations. Businesses must ensure appropriate use cases for generative AI, backed by the right technology and safety measures, to mitigate these concerns. Nearly half of consumers (45%) are calling for regulatory measures on AI usage.
Ethical Concerns and Risks in Generative AI Use
Ethical concerns and risks are major issues for both business leaders and consumers. Over half of the general public (53%) oppose the use of generative AI in making ethical decisions, and 41% of business respondents are wary of its application in critical decision-making areas. Consumers particularly oppose its use in politics (46%), while businesses are cautious about deploying it in healthcare (40%).
Research findings highlight worrying gaps in organizational practices. Only a third of business leaders ensure the data used to train generative AI is diverse and unbiased. Furthermore, only 36% have set ethical guidelines, and 52% have established data privacy and security policies for generative AI applications.
This lack of emphasis on data integrity and ethical considerations puts firms at risk. Ethics is a major concern for 63% of business leaders, followed closely by data-related issues (62%). Better governance is essential to create confidence and mitigate risks related to generative AI use in the workplace.
The Rise of Generative AI Skills and the Need for Enhanced Data Literacy
As generative AI evolves, developing relevant skill sets and enhancing data literacy are crucial for realizing its full potential. Consumers increasingly use generative AI for information retrieval, email communication, and skill acquisition. Business leaders report using generative AI for data analysis, cybersecurity, and customer support. Despite the success of pilot projects, challenges like security problems, data privacy issues, and output quality and reliability remain.
Trevor Schulze, Alteryx’s CIO, emphasized the need for both enterprises and the general public to fully understand AI’s value and address common concerns as they navigate the early stages of generative AI adoption.
Schulze highlighted the importance of addressing trust issues, ethical concerns, skills shortages, privacy fears, and algorithmic bias. He underscored the necessity for enterprises to expedite their data journey, adopt robust governance, and enable non-technical individuals to access and analyze data safely and reliably. Addressing privacy and bias concerns is crucial for genuinely profiting from this game-changing technology.