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Research and Executive Reading

Published research selected for executive practice.

Research and Executive Reading brings together published articles and professional guidance on organizational friction, executive capacity, responsible AI, and measurement. ClarityPlan selects these resources and explains their relevance to executive practice. Each entry credits the original authors, links to the publication, and identifies important limits on interpretation.

ClarityPlan is the curator and interpreter of this collection. Authorship of each publication remains with its original authors; citing a source does not establish affiliation, endorsement, or validation of ClarityPlan’s methods.

Research and Executive Reading connects you with published work by outside authors. ClarityPlan Executive Insights presents Willis F. Kettrell’s analysis of leadership, organizational friction, and responsible AI.

ClarityPlan Executive Insights

Understanding Organizational Friction

Management article

Why AI Customer Journeys Need More Friction

Renée Richardson Gosline · Harvard Business Review · June 9, 2022

HBR access restrictions may apply. Summary and application written by ClarityPlan; no endorsement by the publisher is implied.

Editorial summary

Gosline distinguishes friction that obstructs people from friction that protects their choices, understanding, and autonomy. She encourages organizations to examine where AI-supported experiences need deliberate checks and greater transparency.

ClarityPlan application

Review one recurring process. Identify steps that create avoidable effort and steps that protect accuracy, informed choice, privacy, or access to human assistance. Test changes against both efficiency and the experience of the people served.

Evidence limits. Published in 2022. Technology examples, forecasts, and statistics reflect that period. This management article offers a framework for examining friction; it does not establish that adding review steps always improves outcomes.

University research explanation

Career Advice: How to Become a “Friction Fixer”

Audrey Kim · Stanford Graduate School of Business · February 1, 2024

Free full text · HTML · Stanford Graduate School of Business
Complete text checked signed out on October 24, 2026; no login or payment required.

Editorial summary

Summarizes advice from Robert I. Sutton and Huggy Rao on subtracting unnecessary work, valuing people's time, using clear language, and preserving useful friction. Staff as well as senior leaders can identify obstacles.

ClarityPlan application

Use this as a reading prompt before examining a recurring approval or reporting process. Ask which steps serve a necessary purpose and which deserve investigation.

Evidence limits. This is a short university article interpreting a management book, not a standalone causal study. Its examples do not establish expected results for a ClarityPlan engagement.

Policy research brief

Strengthening NYC’s Nonprofits by Reducing Administrative Burdens

Charlotte Crowe with Ben Rosenn · Center for an Urban Future · January 2023

Free full text · HTML · Center for an Urban Future
Complete text checked signed out on October 24, 2026; no login or payment required.

Editorial summary

Drawing on nearly 40 interviews with human-services nonprofit leaders, this brief examines duplicative contracting, reporting, reimbursement, and audit requirements. It proposes ways to reduce unnecessary administrative work while preserving accountability.

ClarityPlan application

Map a recurring reporting or approval process. Identify duplicated submissions, unclear requirements, and time diverted from service delivery; ask which changes would reduce effort without weakening necessary oversight.

Evidence limits. This is a policy brief about New York City human-services nonprofits, not a controlled study. Its interview findings and 2023 recommendations do not establish current conditions elsewhere or expected results for a ClarityPlan engagement.

Practical reflection

Which step should we remove because it wastes effort—and which step should we preserve because it protects someone?

Want to apply this reading to a recurring challenge in your organization? Discuss your needs with Willis, your executive thought partner for practical leadership and responsible AI use.

Discuss a Weekend Executive Working Session

Technology and Executive Capacity

University research explanation

10 levers for shaping generative AI that truly improves worker performance

Seb Murray · MIT Sloan Ideas Made to Matter · September 3, 2026

Free full text · HTML · MIT Sloan
Complete text checked signed out on October 24, 2026; no login or payment required.

Editorial summary

This article explains a report from MIT’s Working Group on Generative AI and the Work of the Future. It connects deployment choices and changes in work with the question of whether jobs improve.

ClarityPlan application

Before choosing software, ask how responsibilities, learning, review, and work allocation will change. Use the article to frame a discussion with staff about the process around the tool.

Evidence limits. This is an explanatory article, not a standalone randomized experiment. The byline belongs to the writer, not the researchers discussed in the text.

Professional guidance

Choosing Your AI Path: A Framework for Nonprofit Leaders to Make Strategic Choices

Nate Wong, Derek Brine, Natalia Alarcon, Paige Boehmcke, Eliza Patterson, and Zach Slobig · The Bridgespan Group · August 20, 2026

Free full text · HTML · The Bridgespan Group
Complete text checked signed out on October 24, 2026; no login or payment required.

Editorial summary

The authors organize AI choices around augmenting organizational capacity, advancing mission, and advocating for responsible development and use. The framework encourages mission-related choices rather than undifferentiated adoption.

ClarityPlan application

Ask which organizational priority the proposed AI use serves and whether the organization can support it. Read alongside cross-sector studies rather than treating nonprofit affiliation as the only selection criterion.

Evidence limits. Professional strategy guidance does not establish a causal performance effect or validate a ClarityPlan engagement.

Want to apply this reading to a recurring challenge in your organization? Discuss your needs with Willis, your executive thought partner for practical leadership and responsible AI use.

Discuss a Weekend Executive Working Session

Responsible AI and Executive Judgment

University research explanation

5 things to consider when working with AI

Sara Brown · MIT Sloan Ideas Made to Matter · June 16, 2026

Free full text · HTML · MIT Sloan
Complete text checked signed out on October 24, 2026; no login or payment required.Complete university explanatory article; not the underlying research papers.

Editorial summary

Summarizes research presented at MIT’s Initiative on the Digital Economy conference on AI design, prompting, workflows, human judgment, and jobs. It highlights ongoing research on asking people to explain why they follow AI recommendations rather than accepting them uncritically.

ClarityPlan application

Before acting on an AI recommendation, document the reasoning and check important claims independently. Examine how prompts frame the advice and where deliberate review belongs in the whole workflow.

Evidence limits. This is a university article summarizing several research presentations, including preliminary and ongoing findings, not a standalone peer-reviewed study. Its examples do not establish expected nonprofit outcomes or justify removing oversight from consequential decisions.

Government guidance

AI Insights: Generative AI (HTML)

Government Digital Service · GOV.UK · Updated August 3, 2026

Free full text · HTML · GOV.UK
Complete text checked signed out on October 24, 2026; no login or payment required.

Editorial summary

Explains generative AI, model selection, reliability, testing, and data management. The guidance warns that human-like language does not demonstrate understanding and describes evaluating outputs against expected answers and relevant risks.

ClarityPlan application

Define a proposed task and its expected result, test representative cases, and decide which outputs require independent checking. Review privacy and organizational policy before sharing information with an AI service.

Evidence limits. This is introductory UK government guidance, not a study of critical-thinking effects or US legal advice. It does not replace testing a specific system or obtaining appropriate advice about sensitive data.

Management article

Why Even Your Best Employees Override AI Systems That Work

Das Narayandas · Harvard Business Review · November–December 2026

Subscription may be required. Summary and application written by ClarityPlan; no endorsement by the publisher is implied.

Editorial summary

Employees may override effective AI systems when they remain personally accountable for outcomes but lack clear organizational backing to follow the system. Narayandas argues that leaders must align decision authority, accountability, and employee roles as AI changes how work gets done.

ClarityPlan application

Before introducing AI, define which tasks and decisions it may perform, when employees should intervene, who explains outcomes, and how leaders will address errors when approved procedures are followed. Examine whether existing review requirements create unnecessary duplicate work.

Evidence limits. This article offers a management argument supported by organizational examples. It does not establish that every AI tool should make autonomous decisions or that human overrides are necessarily inappropriate.

Related reading

Why AI Customer Journeys Need More Friction

Renée Richardson Gosline · Harvard Business Review

Want to apply this reading to a recurring challenge in your organization? Discuss your needs with Willis, your executive thought partner for practical leadership and responsible AI use.

Explore the Weekend Executive Leadership Lab

Measuring Whether Work Improved

University research explanation

Study finds ChatGPT boosts worker productivity for some writing tasks

Zach Winn · MIT News · July 14, 2023

Free full text · HTML · MIT News
Complete text checked signed out on October 24, 2026; no login or payment required.Complete university explanatory article; not the underlying research paper.

Editorial summary

Explains Shakked Noy and Whitney Zhang’s experiment with 453 professionals completing writing tasks. The study measured completion time and quality assessed by evaluators unaware of AI use; the article also explains why factual checking and organizational context matter when applying the findings.

ClarityPlan application

Compare a small assisted workflow with the existing method using agreed quality criteria as well as completion time. Include fact-checking, review effort, and rework rather than treating a faster draft as a finished improvement.

Evidence limits. This is MIT’s explanatory article, not the underlying Science paper. The experiment used short, explicitly defined tasks without company-specific context or fact-checking; its results do not establish expected nonprofit savings or performance for current models.

University research explanation

NNSI Research Report: The Nonprofit Capacities Instrument

Katherine Cooper · Network for Nonprofit and Social Impact, Northwestern University · Undated — summarizes a 2017 study

Free full text · HTML · Northwestern University
Complete text checked signed out on October 24, 2026; no login or payment required.Complete university explanatory article; not the underlying 2017 research paper.

Editorial summary

The article explains research that treats nonprofit capacity as several distinct capacities. It describes an instrument developed and tested across organizations rather than equating capacity with one general impression.

ClarityPlan application

Identify which capacity a proposed change should affect, such as operational capacity or staff management. Do not claim that ClarityPlan’s own reflection tool inherits the instrument’s validation.

Evidence limits. No publication date is visible for the university article. Underlying study: Shumate, Cooper, Pilny, and Peña-y-Lillo (2017), Nonprofit Management and Leadership, 28(2), 155–174.

Want to apply this reading to a recurring challenge in your organization? Discuss your needs with Willis, your executive thought partner for practical leadership and responsible AI use.

Discuss How to Evaluate Your Workflow

Corrections

If you spot an error in a title, author line, date, or link, please let us know at wfkettrellenterprises@gmail.com. Access can change; the signed-out check date is shown with each entry.