Technology

AI adoption accelerates but ethical and cultural challenges threaten to deepen inequality

Sunday, 26 October 2025 5:02AM UTC

As 78% of organisations now employ AI across sectors, experts warn that without ethical frameworks and human-centric policies, AI could exacerbate inequality and undermine worker well-being, despite its transformative potential for innovation.

Artificial intelligence (AI) has transitioned from an aspirational concept to an integral part of modern business operations. According to data from McKinsey and various industry reports, 78% of global organisations now employ AI in at least one business function, demonstrating its widespread adoption across sectors such as telecommunications, finance, and retail. This rapid integration is also evident among smaller businesses, with 89% of small US companies utilising AI for routine tasks. Despite this expansion, many organisations remain cautious in moving beyond pilot projects, with 68% reporting that less than 30% of their AI experiments have progressed into full-scale operational deployment.

After three decades dedicated to policy-making, Ana Paula Vescovi’s recent academic pursuit at Wharton Business School delves into management and leadership amidst AI’s rise, focusing on the intersection of technology, strategy, and workplace psychology. Vescovi underscores the lack of consistent metrics to evaluate AI’s return on investment, particularly with generative AI, revealing a disconnect between the race for efficiency and the understanding of its broader impacts. This gap highlights a critical organisational choice: whether to use AI to replace human workers for quick gains or to augment human capabilities for enduring innovation and trust.

The broader economic history reminds us, as scholars Daron Acemoglu and Simon Johnson have noted, that technological progress is not inherently equitable or beneficial to all. Technological advancement can either concentrate power and exacerbate inequality or distribute opportunities and foster well-being and growth. This dual potential is mirrored in today’s AI deployment, which redefines work by automating tasks that once showcased human talent, possibly eroding worker autonomy, competence, and the social fabric of the workplace.

Work psychology identifies three pillars essential for employee well-being and productivity—learning, autonomy, and belonging. Research cited by Vescovi, including studies by Professor Stefano Puntoni, indicates that AI’s current implementations often reduce empathy and altruism among workers, and consumers tend to value products more when human involvement is apparent. Hence, the technology itself is less decisive than the design of human-AI interactions, which must translate organisational culture into ethical standards and measurable outcomes.

Generative AI also offers a transformative potential for innovation. Christian Terwiesch of Wharton describes “innovation tournaments” enabled by AI, where broader participation in ideation and problem-solving is encouraged, with humans acting as curators rather than mere executors. This shift combines machine speed with human judgment, creating new competitive advantages for companies that can effectively balance these forces.

The future success of AI-driven innovation depends not merely on technology but on the cultural frameworks that surround it. Companies that foster structured experimentation alongside creative freedom can generate not only products but also meaningful progress. Vescovi suggests that AI’s promise lies in restoring human time and energy for reflection and reinvention, provided that fair transition policies support those impacted and continuous learning is prioritised.

The ultimate trajectory of AI’s societal impact hinges on economic incentives, public policy, and market valuation of human-centric investments. If systems focus exclusively on short-term productivity, AI use is more likely to replace workers and concentrate wealth. Conversely, valuing human development and knowledge dissemination could make AI a catalyst for shared prosperity. Thus, collaboration between companies and regulators is essential to align technical advancements with social and economic progress.

In conclusion, AI embodies the potential for either widespread abundance or deepening inequality. The determining factor will not be the sophistication of algorithms themselves but the collective human choices, ethical frameworks, and incentives constructed around them.

📌 Reference Map:

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Source: Noah Wire Services

More on this

https://lnginnorthernbc.ca/2025/10/26/power-and-progress-in-the-era-of-artificial-intelligence-10-25-2025-ana-paula-vescovi/ - Please view link - unable to able to access data
https://www.theglobalstatistics.com/artificial-intelligence-ai-usage-statistics/ - This article provides comprehensive statistics on global AI adoption in business as of 2025. It reports that 78% of companies worldwide are using AI in at least one business function, marking a significant increase from previous years. The adoption rates vary across industries, with the telecommunications, finance, and retail sectors leading the way. The article also highlights the rapid growth of AI usage among small businesses, with 89% of small US businesses utilizing AI for everyday operational tasks. Additionally, it discusses the challenges organizations face in transitioning from AI experimentation to full-scale deployment, noting that 68% of companies have yet to move more than 30% of their AI experiments into operational deployment.
https://xtendedview.com/ai-in-business-statistics/ - This article presents statistics on AI adoption in business as of 2025. It reports that 78% of organizations are using AI in at least one function, up from approximately 55% in 2023. The article also notes that 69% of organizations use generative AI in at least one business function, and about 35% of businesses globally have fully deployed AI in one function. It highlights that 42% are actively piloting AI tools, and across all companies, 77% are either using or exploring AI. The article also discusses the barriers to AI adoption, citing cost and lack of technical skill as common challenges.
https://www.allaboutai.com/resources/ai-statistics/workplace/ - This article provides insights into AI adoption in the workplace as of 2025. It reports that 78% of global companies have integrated AI into at least one business function, with significant variation by industry and company size. The article also notes that 71% of organizations are using generative AI in at least one business function, up from 65% in early 2024. It highlights that healthcare, manufacturing, and IT sectors are experiencing the most dramatic year-over-year growth in adoption rates. The article also discusses the anticipated growth of the AI industry, projecting it will soar to $407 billion by 2027, up from $86.9 billion in 2022.
https://www.hostinger.com/tutorials/how-many-companies-use-ai - This article provides statistics on AI adoption among companies as of 2025. It reports that 78% of companies have adopted AI technologies, a significant increase from previous years. The article also notes that companies are now using AI in an average of three different functions, reflecting a more sophisticated approach to AI integration. It highlights that 89% of small businesses use AI tools for everyday tasks, indicating that AI tools have become sufficiently accessible and affordable for companies regardless of size. The article also discusses the challenges companies face in transitioning from experimentation to full production, noting that 68% of companies report that fewer than 30% of their AI experiments have moved into operational deployment.
https://seosandwitch.com/ai-in-business-transformation-statistics/ - This article presents statistics on AI adoption in business transformation as of 2025. It reports that 77% of businesses are either using or exploring AI, up from 54% in 2020. The article also notes that 35% of companies globally report actively using AI in their business operations. It highlights that AI adoption is highest in China (58%), followed by India (57%) and the U.S. (25%). The article also discusses the projected growth of AI-related spending worldwide, which reached $154 billion in 2023 and is projected to grow to $300 billion by 2026.
https://www.mckinsey.com/featured-insights/week-in-charts/gen-ais-broad-reach - This article discusses the broad reach of generative AI across industries as of April 2025. It reports that 71% of companies are using generative AI in at least one business function. The article highlights that generative AI is most used in marketing and sales among all industries surveyed, with technology leading the way in adopting generative AI across all functions. It also notes that product and service development is the second-most-common use, heavily adopted by professional services. The article provides data on the percentage of respondents in various industries whose organizations regularly use generative AI in different business functions.

Noah Fact Check Pro

The draft above was created using the information available at the time the story first emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed below. The results are intended to help you assess the credibility of the piece and highlight any areas that may warrant further investigation.

Freshness check

Score: 8

Notes: The narrative appears to be original, with no evidence of prior publication. The earliest known publication date of similar content is October 26, 2025. The report includes updated data but recycles older material, which may justify a higher freshness score but should still be flagged. The narrative is based on a press release, which typically warrants a high freshness score. However, if earlier versions show different figures, dates, or quotes, these discrepancies should be flagged. If anything similar has appeared more than 7 days earlier, this should be highlighted explicitly.

Quotes check

Score: 9

Notes: The quotes attributed to Ana Paula Vescovi and other individuals are not found in earlier material, suggesting they are original or exclusive content. No identical quotes appear in prior publications. If quote wording varies, note the differences. If no online matches are found, raise the score but flag as potentially original or exclusive content.

Source reliability

Score: 6

Notes: The narrative originates from LNG in Northern BC, which is an obscure, unverifiable, or single-outlet source, leading to uncertainty about its reliability. If the narrative originates from a reputable organisation (e.g., Financial Times, Reuters, BBC), note this as a strength. If it originates from an obscure, unverifiable, or single-outlet narrative, flag the uncertainty. If a person, organisation, or company mentioned in the report cannot be verified online (e.g., no public presence, records, or legitimate website), flag as potentially fabricated.

Plausability check

Score: 7

Notes: The claims about AI adoption rates and the perspectives of Ana Paula Vescovi are plausible and align with current industry trends. However, the lack of supporting detail from other reputable outlets and the absence of specific factual anchors (e.g., names, institutions, dates) reduce the score and flag the report as potentially synthetic. If the narrative lacks supporting detail from any other reputable outlet, flag this clearly. If the report lacks specific factual anchors (e.g., names, institutions, dates), reduce the score and flag as potentially synthetic. If language or tone feels inconsistent with the region or topic—e.g., strange phrasing, wrong spelling variant—flag as suspicious. If the structure includes excessive or off-topic detail unrelated to the claim, note this as a possible distraction tactic. If the tone is unusually dramatic, vague, or doesn’t resemble typical corporate or official language, flag for further scrutiny.

Overall assessment

Verdict (FAIL, OPEN, PASS): OPEN

Confidence (LOW, MEDIUM, HIGH): MEDIUM

Summary: The narrative presents original quotes and plausible claims but originates from an obscure source, lacks supporting details from reputable outlets, and includes recycled material, leading to an overall assessment of 'OPEN' with medium confidence.

Artificial Intelligence
Workplace Psychology
Ethics