Towards an AI Governance Stucture for Business

APA's PsycArticles contains more than 250,000 full text research articles in psychology but many of these articles have real world business implications relevant to researchers and students in academic disciplines outside psychology and social sciences. Here is an interesting example on Artificial Intelligence.

A recently published article in Artificial Intelligence and Organizational Strategy: Ethical and Governance Implications by Larry W. Norton (Consulting Psychology Journal, Vol 77(2), Jun 2025, 131-141) addresses not just how AI will fundamentally redefine work but how we must implement governance and take management responsibility to manage outcomes – both intended and unintended.

As Norton’s research makes clear, AI is not just about automation; AI is shaping strategy, driving innovation, and changing the definition of everything from customer value to product development. Referencing several AI use cases including CapitalOne and Mayo Clinic, Norton proffers that if you’re not thinking about AI strategically, you’re already behind.

There are real risks—algorithmic bias, data privacy, even unintended societal harm and the article is clear we need to be smart about how AI is deployed, balancing the pursuit of profit with responsible implementation, starting with low-risk, high-impact use cases and scaling up responsibly as capabilities mature. Even a casual awareness of how AI has dominated recent business and economic commentary would make clear that we must be smart about how AI is deployed.  This is where Norton offers a formula – based on research – for corporations to manage their AI implementations and make governance not simply a ‘nice to have’ but a business imperative.

The author lays out what effective AI governance looks like: everything from ensuring data quality to having clear stakeholder accountability, regulatory compliance and crucially, ethical oversight. Norton references established frameworks like the National Institute of Standards andTechnology’s AI Risk Management Framework and the IEEE’s Ethically Aligned Design, stressing transparency, explainability, fairness, and accountability in AI systems.

Norton suggests three key recommendations:

• treat AI risk mitigation as a competitive differentiator,
• tailor governance models to the ethical and business risks of specific AI applications,
• start small and scale responsibly

He also calls for increased AI literacy among consultants and organizational leaders, arguing that understanding AI’s capabilities and limitations are essential for ethical and effective deployment and significantly that AI oversight needs to go right up to board level particularly in firms where AI development and/or implementation is central to the business strategy.

Find this article: Consulting Psychology Journal, Vol 77(2), Jun 2025, 131-141 

A sample of further PsycArticle readings on the intersection of psychology and Artificial Intelligence  include:

• How and for whom using generative AI affects creativity: A field experiment. 
• Unethical and harmful effects of artificial intelligence on human interactions and well-being: What organizational consultants can do.
• Consultants’ and managers’ ethical and legal responsibilities in artificial intelligence applications.

More information about APA products and subscription options is located here.

DC US Attorney Sends Query Letters to Academic Publishers about Research Practices

Given our current political environment this outreach by the US Attorney for DC has been widely anticipated by many in the academic publishing community. Unknown is how many similar letters have been sent (if any).  What this requests suggests is that, in the view of the DC court, publishers have been tipping the scales in the conduct and publication of research such that they have a bias contrary to the views and assumptions of the republican administration and/or those on the right generally.

On the surface, there isn't much illegitimate about these questions: they are valid; however, the purpose for asking them and the interpretation of the answers is where academic and association publishers may have legitimate concerns.

 

Federal Reserve Report on High Ed Institution Viability - It is Bleak.

There has been a decades long (at least) discussion about the viability of a certain segment of the higher education institution market and assumptions there would be a significant contraction in the number of schools. Now, things may have taken a turn for the worst. This report by the Federal Reserve (published before trumpocomics) anticipated an acceleration in the closure of 'at risk' schools. These are primary schools with small enrollments, a dependency on tuition for revenue and with limited or no endowment.

I used Copilot to create this summary:

1. Enrollment Declines and Financial Distress: The report highlights that enrollment declines, particularly due to the "demographic cliff" and the COVID-19 pandemic, are significant predictors of financial distress and college closures. ​ Enrollment fell by 15% from 2010 to 2021, and the trend may continue, exacerbating financial challenges for institutions. ​
2. Predictive Models for College Closures: The authors developed predictive models using machine learning techniques, which significantly outperform traditional linear probability models and existing federal accountability metrics. ​ The preferred model, using the XGBoost algorithm, showed an 84% accuracy rate in predicting closures within three years for the riskiest institutions. ​
3. Impact of Missing Data: A high degree of missing data among colleges that eventually close is a key impediment to identifying at-risk institutions. ​ Machine learning models, particularly XGBoost, are more effective at handling incomplete data and improving predictive accuracy compared to traditional methods. ​
4. Financial Metrics and Predictive Accuracy: Key financial metrics such as operating margin, debt levels, and changes in revenue and expenses are strong predictors of college closures. ​ The machine learning models demonstrated that ratios of financial metrics and changes in these metrics are more important than absolute levels for predicting closures.
5. Future Closure Predictions: Simulations based on the predictive models suggest that the demographic cliff could significantly increase annual college closures. ​ Under worst-case scenarios, there could be up to 80 additional closures annually, affecting over 100,000 students and 20,880 staff members, highlighting the potential widespread impact on local communities and economies.

According to Best Colleges, over 75 institutions have closed, merged or announced closure since the start of COVID and they estimate this had impacted almost 50,000 students.

From the report:

These financial pressures on higher education have elevated financial distress — up to and including closures — as a major higher education policy issue. While there have been predictions of a wave of closures for the last decade (e.g., Eide, 2018; Horn, 2018), most colleges survived the pandemic thanks to timely federal support and emergency actions taken to freeze or reduce personnel costs (Natow, 2021). However, the withdrawal of pandemic-era federal funding, along with existing stressors, likely resulted in an increase in closures during 2023 (Sanchez, 2024) and into 2024. There has also been a wave of colleges declaring financial exigency, eliminating academic programs and employees in an effort to cut costs and to avoid potential closures (Ambrose & Nietzel, 2024). Even flagship universities such as West Virginia University and Pennsylvania State University have pursued sizable reductions in the number of academic programs as they face budget deficits (Burke, 2024; Povich, 2023).

Unmentioned in this report is the negative impact of international students which typically pay much higher tuition fees. While international students may not be a target cohort for the schools in this 'at risk' group it is possible that an overall decrease in international students could expand this 'at risk' group (make it larger). Additionally, smaller schools often rent out their campus to foreign student programs for English and cultural programs during summer recess but it is entirely possible that these programs will dry up if they haven't already done so. The forecast may be bleak.