Technology, Informatics, and Artificial Intelligence in Healthcare

The AONL Foundation envisions a healthier tomorrow advanced through nursing leadership and strives to achieve that vision by providing resources to create opportunities to bridge science and practice to shape the future of nursing leadership.

The Foundation supports the AONL vision of advancing health for all. Priority will be given to studies focused on the responsible implementation, evaluation, governance, and scaling of healthcare technology, informatics, and artificial intelligence (AI) through nursing leadership. Proposed studies should demonstrate how nurse executives, including chief nursing officers, vice presidents of nursing, chief nurse informaticists, and other senior nurse leaders, can guide technology-enabled transformation while protecting quality, safety, workforce well-being, and patient-centered care.

Proposals should align with AONL strategic priorities, including:
 

• Lead, inspire, and support the healthcare workforce
• Advance nursing leadership
• Improve health through advocacy
   

Artificial intelligence (AI): Computer-based systems designed to perform tasks that typically require human intelligence, including prediction, classification, pattern recognition, natural language processing, decision support, workflow automation, and generative AI.¹ Generative AI: AI systems that can create new text, images, summaries, recommendations, or other outputs based on prompts or data inputs. In healthcare, generative AI may be used to support documentation, patient education, administrative workflows, clinical knowledge synthesis, or communication, but requires careful oversight.²
Healthcare informatics: The use of information, data, knowledge, technology, and workflow design to improve healthcare delivery, patient outcomes, population health, operational performance, and the experience of patients and clinicians.³
Responsible AI: The design, procurement, implementation, monitoring, and governance of AI in ways that promote safety, transparency, reliability, privacy, security, accountability, fairness, and human oversight.⁴
AI governance: The policies, structures, decision rights, oversight processes, metrics, and accountability mechanisms used to guide the selection, implementation, monitoring, and evaluation of AI systems across an organization.⁵
Nurse executive or senior nurse leader: A nursing leader with formal responsibility for care delivery, nursing practice, workforce strategy, quality, safety, informatics, operations, or organizational policy. Examples include chief nursing officers, vice presidents of nursing, chief nurse informatics officers, associate chief nurses, and comparable roles across health systems, including ambulatory care, long-term care, public health, community health, and other settings.⁶

Healthcare organizations are increasingly adopting digital technologies, advanced analytics, virtual care models, automation, and AI-enabled tools to improve care delivery, support clinical decision-making, strengthen operations, and address workforce challenges. These technologies create significant opportunities for nursing leadership, but they also introduce complex implementation challenges related to safety, reliability, bias, privacy, cybersecurity, workflow integration, accountability, transparency, patient trust, clinician trust, and workforce impact.

Nurse leaders are uniquely positioned to ensure that technology and AI implementation is grounded in clinical realities, patient and family needs, interprofessional collaboration, and the ethical obligations of individual practitioners and healthcare organizations. Chief nursing officers, vice presidents of nursing, chief nurse informaticists, and other senior nurse leaders shape care delivery models, staffing, practice environments, quality and safety systems, workforce development, and organizational culture. Their leadership is essential to ensure that AI augments professional judgment, supports care teams, improves outcomes, and advances health for all.

Through this Request for Proposals (RFP), the AONL Foundation invites research proposals that examine how nursing leaders can implement, govern, evaluate, and scale informatics, technology, and AI in healthcare. Funded research projects should generate actionable knowledge, scalable strategies, implementation frameworks, leadership competencies, governance models, or measurable outcomes that can inform nursing leadership practice nationally.

AONL seeks proposals that support innovative, evidence-informed, and leadership-driven approaches to the responsible use of informatics, technology, and AI in healthcare. Proposals should emphasize the role of nurse leaders in driving transformation at the organizational, system, workforce, patient care, or community level. Projects may focus on hospitals, health systems, ambulatory care, behavioral health, long-term care, public health, community-based care, or other healthcare settings.

Areas of interest include, but are not limited to:

1. Nursing Leadership, Governance, and Strategy for AI
   1. Models for nurse executive leadership in AI governance, technology selection, procurement, oversight, and accountability.
   2. Decision-making structures that clarify the role of CNOs, VPs of nursing, chief nurse informaticists, clinical leaders, patients, information technology leaders, data science teams, quality and safety leaders, compliance, legal, and vendors.
   3. Development or evaluation of nursing leadership competencies for responsible AI and digital transformation.
       
2. Workforce Readiness, AI Literacy, and Change Management
   1. Leadership strategies to prepare nurses and interprofessional teams to use AI-enabled tools safely, effectively, and ethically.
   2. Approaches to build AI literacy, informatics competencies, psychological safety, clinician trust, and human oversight.
   3. Evaluation of how AI implementation affects nursing workload, documentation burden, staffing, burnout, professional practice, team communication, and workforce well-being.
       
3. Quality, Safety, and Clinical Outcomes
   1. Implementation or evaluation of AI-enabled tools intended to improve patient safety, early recognition of deterioration, care coordination, infection prevention, medication safety, falls prevention, discharge planning, documentation quality, or other clinical outcomes.
   2. Leadership-led monitoring of algorithm performance, model drift, unintended consequences, alert burden, human factors, and workflow fit.
   3. Methods to ensure AI augments, rather than replaces, nursing judgment and clinical decision-making.
       
4. Access and Patient-Centered Care
   1. Use of technology or AI to improve access, patient engagement, care navigation, language access, culturally informed care, rural health, home-based care, community-based care, or population health.
   2. Leadership strategies to mitigate AI’s impact on worsening disparities and to monitor outcomes across race, ethnicity, language, age, gender, disability, socioeconomic status, geography, and other relevant groups.
   3. Patient, family, community, and frontline clinician engagement in the design, implementation, and evaluation of technology and AI tools.
       
5. Informatics Infrastructure, Data, Measurement, and Accountability
   1. Leadership approaches to improving data quality, interoperability, documentation standards, EHR integration, clinical workflow design, and governance of data used in AI systems.
   2. Dashboards, metrics, and accountability structures for measuring technology adoption, safety, effectiveness, usability, workforce outcomes, and return on investment.
   3. Use of implementation science methods to evaluate adoption, adaptation, fidelity, sustainability, and scale across units, sites, or systems.
       
6. Policy, Ethics, Regulation, and Sustainability
   1. Nursing leadership engagement in organizational policy, advocacy, regulatory readiness, vendor accountability, privacy, cybersecurity, and ethical governance related to AI and technology.
   2. Frameworks for transparency, informed use, human oversight, escalation pathways, incident reporting, and accountability when AI outputs influence care decisions or operational decisions.
   3. Sustainable financing, reimbursement, partnership, and academic-practice-industry models that support responsible digital transformation led by nurse leaders.
       

Proposals must not exceed 10 pages, single-spaced with 1-inch margins in Times New Roman or Arial 12-point font, excluding references and appendices, and should include the following components:

1. Project Summary (500 words, not included in the 10-page limit)
   1. Overview of the problem, proposed study, technology or AI focus, leadership role, setting, and anticipated impact.
       
2. Statement of Problem
   1. Description of the issue being addressed, supported by data, literature, organizational evidence, or practice-based need.
   2. Relevance to nursing leadership and alignment with AONL’s mission, vision, and strategic priorities.
   3. Description of why nurse executive leadership is essential to successful and responsible implementation.
       
3. Project Description and Approach
   1. Goals, research aims, questions, hypotheses, or objectives.
   2. Description of the technology, informatics intervention, AI-enabled tool, governance model, implementation strategy, or leadership intervention being studied.
   3. Conceptual model, implementation science framework, informatics framework, AI governance framework, or leadership framework guiding the study.
   4. Research design and methods, including setting, sample, recruitment, measures, data sources, analytic plan, and timeline.
   5. Role of nurse leaders and key partners, including clinical nurses, patients/families, informatics, IT, data science, quality/safety, compliance, ethics, legal, finance, and vendor partners as applicable.
   6. Description of the novel concept, approaches, methodologies, and interventions being studied or guiding the study. 
       
4. Impact
   1. How the project will advance nursing leadership in technology and AI implementation.
   2. How the project will improve patient outcomes, quality, safety, access, care experience, workforce outcomes, operational performance, or organizational readiness.
   3. Populations, workforce groups, care settings, or communities expected to benefit.
       
5. Evaluation and Outcomes
   1. Measures of success and plans for evaluation.
   2. Plans to assess usability, workflow integration, clinician trust, human oversight, unintended consequences, algorithm performance, safety, sustainability, and scalability as applicable.
   3. Use of qualitative, quantitative, mixed-methods, or implementation science metrics to assess progress and impact.
       
6. Dissemination and Sustainability
   1. Plans to share findings, tools, frameworks, implementation guides, governance templates, policy recommendations, or lessons learned with the broader nursing leadership community.
   2. Plans to embed findings in organizational policy, advocacy, workforce development, leadership education, or future research.
   3. Potential for scalability or sustainability beyond the funding period.
       
7. Budget and Budget Justification
   1. Detailed budget and justification for all requested funds.
       
8. Project Team and Organizational Capacity
   1. Qualifications of the project team.
   2. Relevant leadership, informatics, AI, implementation science, quality improvement, research, evaluation, policy, ethics, or data science expertise.
   3. Organizational resources, data access, leadership support, and implementation capacity.
       

• Grants available:                     Two (2) grants of $15,000
• Online Submissions Open:      August 25, 2026
• Deadline for Submissions:      October 14, 2026
• Grant Notification:                   December 2026
• Public Announcement:            January 2027
• Funding Dates:                       February 2027 - March 2028
• Project Completion:                Study completed within 18 months, inclusive of dissemination planning

Please note: a portion of the funds will be distributed at the beginning of the funding period. Remaining funds are dependent upon and will be distributed at completion of the study. The timeframe should allow for the possibility of presentation at a future AONL Annual Conference. The project may be completed at any point within the established timeframe.

• Principal investigator must be a current licensed Registered Nurse.
• One or more members of the research team must be an AONL member.
• Priority will be given to proposals that include a nurse executive, such as a CNO, VP of nursing, chief nurse informaticist, or comparable senior nurse leader, as PI, co-investigator, organizational sponsor, or implementation partner.
• Members of the board of directors, officers, and staff of the AONL Foundation, AONL, the American Hospital Association, and its affiliates are not eligible to apply.
• Principal investigators currently funded by the AONL Foundation are not eligible for this award.

• AONL Foundation can only provide grants to recipients in the United States and its territories.

   

• This grant award applies only to research studies, including implementation science, health services research, mixed-methods studies, evaluation studies, and leadership-focused research. Operational implementation projects without a research design are not eligible.
• Documentation of Institutional Review Board (IRB) approval, exemption, or a timetable for IRB determination is required prior to initiation of funding.
• Implementation of the research project must commence immediately upon receipt of funds.
• The research project must be completed within the established timeframe, inclusive of dissemination.
• Dissemination should include presentation at a national conference and submission of a manuscript for publication in a peer-reviewed journal. A webinar, toolkit, leadership briefing, implementation guide, policy statement, governance framework, or advocacy tool may also be considered.
• If planning to submit an abstract to present at an AONL Annual Conference, that abstract should include the completed study.
• A portion of the award money will be dependent upon completion of the award study.
• The AONL Foundation and underwriting donor should be acknowledged in all publications and presentations that use or reference the findings.

Budget proposals:

• AONL Foundation provides funding for direct expenses and allows up to 10% of total grant funds to be used for indirect expenses or overhead expenses.
• Investigator time will not be supported. All other research-related expenditures, including salary support for research assistants, statisticians, data analysts, informatics support, software, transcription, participant incentives, supplies, communication, and expenses related to presenting study findings at conferences are acceptable expenses.
• Budgets may include costs associated with evaluation, implementation measurement, data extraction, data analysis, usability assessment, qualitative analysis, and dissemination.
• Budgets may not be used to purchase, deploy, or license large-scale AI or technology platforms unless the cost is directly related to the research design and justified as necessary for the study.
   

An electronic copy (Microsoft Word or PDF) of the entire proposal shall be submitted online via AONL Foundation’s website. Applications should be no longer than 10 single-spaced pages with 1-inch margins in Times New Roman or Arial 12-point font, excluding references and appendices. Copies of planned surveys, interview guides, data collection instruments, implementation tools, governance templates, or measures should be included as appendices.

A second copy (Microsoft Word or PDF) of the entire proposal, with all identifying information of researchers and institutions removed, shall also be submitted. The same page limit applies.

Format of Proposal

Please note: All elements listed below are required for consideration of this grant award.

Title Page:

• Name, title, organizational affiliation, email address, phone number, and address of each investigator
• Project title
• Name and role of the nurse executive or senior nurse leader engaged in the study
• Name of organization or setting where the study will be conducted

Proposal:

• Abstract: The abstract needs to provide a brief but comprehensive summary of the contents of your paper. Limit your abstract to 250 words maximum. (Not included in the 10-page limit)
• Project Summary (500 words maximum; not included in the 10-page limit)
   
• Statement of Problem (Background/Literature Review)
• Project Description and Approach
• Conceptual Model, Implementation Science Framework, Informatics Framework, AI Governance Framework, or Leadership Framework
• Specific Aims/Purpose of Study
• Research Design and Methods (setting, sample, measures, data sources, plans for data analysis)
• Description of technology, informatics, or AI intervention or implementation issue being studied
• Role of nursing leadership in implementation, governance, evaluation, or sustainability
• Alignment with AONL Strategic Priorities
• Impact: contribution to nursing leadership, health systems, workforce, care delivery, patient outcomes, and future research
• Plans for Protection of Human Subjects, including privacy, data security, and responsible use of patient, clinician, and organizational data
• Plans for Dissemination and Sustainability, including translation and potential implementation of findings
• Timeline
• Budget
• References

Support Documents:

• Two letters of support, with at least one letter of support from the organization at which the study will be conducted and, when applicable, one letter from a nurse executive or senior nursing leader sponsoring the work.
• Letter of IRB approval or exemption, or timeline for obtaining IRB approval or exemption.
• Instruments, interview guides, survey tools, data collection forms, usability measures, evaluation dashboards, governance tools, or other measures to be used in the study.
• Proof of author permission to use proposed instruments, if applicable.
• Curriculum Vitae or biosketch for each investigator.
• Declaration of any other funding sources for this project.
• Letter or documentation confirming access to required data, technology environment, analytic support, or organizational approvals, if applicable.
• Description of vendor relationship, technology ownership, conflicts of interest, or data use agreements, if applicable.
   

All submitted proposals will undergo a blind review by members of the AONL Foundation Board of Directors Research Review Committee. The grant award recipients will be selected based on consideration of eligibility and merit of the research proposal. Review criteria will include:

• What is the overall impact of the proposed research study on the defined purpose of advancing responsible technology and AI implementation through nursing leadership?
• What is the significance and innovativeness of the planned study?
• Does the study address an important leadership, informatics, technology, AI, workforce, quality, safety, or implementation gap?
• Is the role of nurse executives or senior nurse leaders clearly defined and central to the study?
• Is the study strategy, methodology, implementation approach, and data analysis plan rigorous and achievable within the projected timeframe?
• Does the proposal include appropriate plans to evaluate safety, effectiveness, usability, workflow fit, workforce impact, governance, sustainability, and unintended consequences as applicable?
• Is the support requested justified and aligned with the proposed research?
• Does the study have potential to generate actionable findings, tools, frameworks, or policy recommendations useful to nurse leaders nationally?

Priority will be given to:

• Research that advances nursing leadership in informatics, technology, and responsible AI implementation.
• Proposals that identify original research opportunities or high-impact replication studies.
• Projects led by or conducted in strong partnership with CNOs, VPs of nursing, chief nurse informaticists, or comparable senior nurse leaders.
• Studies with potential for scalability across units, organizations, care settings, communities, or health systems.
• Projects that address access, safety, workforce well-being, patient-centeredness, transparency, and accountability.
• Projects likely to produce practical deliverables, such as AI governance models, implementation guides, nurse leader competency frameworks, dashboards, policy briefs, advocacy tools, or decision-making templates.

Previous research completed and research experience will be taken into account.
 

• At the beginning of the grant period, the principal investigators will provide a jpg headshot and a narrative biography of no more than 300 words for each investigator.
• At the midpoint and at the conclusion of the research study, the principal investigators will submit interim and final reports, respectively, on the progress and findings of the study.
• At quarterly intervals, principal investigators and study team will meet with AONL Foundation staff and a member of the Research Committee designated as the study’s research liaison. These informal check-in meetings will help keep everyone apprised of the study and current status.
• Upon conclusion of the study and within the established timeline, the principal investigator will submit an abstract and, if accepted, present study findings at a national conference.
• Submit a manuscript for publication to at least one peer-reviewed nursing, informatics, health services research, implementation science, leadership, or healthcare quality journal.
• Submit a summary of the study to be added to the AONL Foundation’s Research Repository.
• Develop a practical leadership deliverable, such as an AI governance guidebook, implementation playbook, policy statement, competency framework, risk assessment tool, evaluation dashboard, advocacy tool, or executive briefing that can be used by nurse leaders.
• Allow study findings to be incorporated into the AONL Foundation’s marketing and communications.
• Aid the AONL Foundation in demonstrating impact of the research.
• Ensure proper acknowledgment of AONL Foundation and the underwriting donor in all publications and presentations.
   

Funding for this research study is made possible thanks to AvaSure. Thank you for your support.

For questions about the submission or review process, please contact the AONL Foundation at aonlfoundation@aha.org. 

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