Artificial intelligence (AI) usually enters organizations as a tool whose work-design implications appear only after implementation. This study shifts the analytic starting point upstream to examine how healthcare AI “makers,” through market-facing narratives, frame AI as suitable for adoption in a regulated, professionally governed field. We ask how technology makers construct and legitimate work-design scripts before organizational implementation. We then analyze public-facing materials from 100 U.S. healthcare AI firms (2023–2026)—including vision statements, product descriptions, and white papers—alongside 19 healthcare trade-journal articles (2023–2025) quoting hospital executives and physician leaders. Using reflexive thematic analysis, we identify three recurring design logics that makers use to frame AI as adoptable: efficiency, which simplifies complexity and boosts productivity; safety, which establishes quality control and risk management; and precision, which ensures accuracy through human oversight. Makers operationalize these logics through three adoption scripts: turnkey solutions that promise rapid deployment and interoperability, configurable solutions that frame bounded rule-setting as a route to governability, and customizable solutions that emphasize partnership and validation for contextual fit. Trade-journal discourse provides demand-side triangulation by framing responsible adoption in governance terms. By showing how technology makers’ scripts direct work organization before implementation even begins, the study advances a theory of upstream work design centered on the marketing of novel technology.
AbbottA. (1988). The system of professions: An essay on the division of expert labor. University of Chicago Press.
2.
AkrichM. (1992). The de-scription of technical objects. In BijkerW. E.LawJ. (Eds.), Shaping technology/building society: Studies in sociotechnical change (pp. 205–224). MIT Press.
3.
BakkerA. B.DemeroutiE. (2007). The job demands–resources model: State of the art. Journal of Managerial Psychology, 22(3), 309–328. https://doi.org/10.1108/02683940710733115
4.
BarleyS. R. (1986). Technology as an occasion for structuring: Evidence from observations of CT scanners and the social order of radiology departments. Administrative Science Quarterly, 31(1), 78–108. https://doi.org/10.2307/2392767
5.
BattR.HermansM. (2012). Global human resource management: Bridging strategic and institutional perspectives. Research in Personnel and Human Resources Management, 31, 1–52. https://doi.org/10.1108/S0742-7301(2012)0000031003
6.
BergM. (1997). Rationalizing medical work: Decision-support techniques and medical practices. MIT Press.
BodenheimerT.SinskyC. (2014). From triple aim to quadruple aim: Care of the patient requires care of the provider. Annals of Family Medicine, 12(6), 573–576. https://doi.org/10.1370/afm.1713
9.
BorupM.BrownN.KonradK.van LenteH. (2006). The sociology of expectations in science and technology. Technology Analysis & Strategic Management, 18(3-4), 285–298. https://doi.org/10.1080/09537320600777002
BraunV.ClarkeV. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806
12.
BrownN.MichaelM. (2003). A sociology of expectations: Retrospecting prospects and prospecting retrospects. Technology Analysis & Strategic Management, 15(1), 3–18. https://doi.org/10.1080/0953732032000046024
13.
ByrneD. (2022). A worked example of braun and clarke’s approach to reflexive thematic analysis. Quality & Quantity, 56(3), 1391–1412. https://doi.org/10.1007/s11135-021-01182-y
FerneleyE. H.SobreperezP. (2006). Resist, comply or workaround? An examination of different facets of user engagement with information systems. European Journal of Information Systems, 15(4), 345–356. https://doi.org/10.1057/palgrave.ejis.3000629
FreidsonE. (2001). Professionalism: The third logic. University of Chicago Press.
23.
GarrettR. G. (2024). AI: A CEO’s perspective. Healthcare Executive, May–June 2024.
24.
GrantA. M.ParkerS. K. (2009). Redesigning work design theories: The rise of relational and proactive perspectives. Academy of Management Annals, 3(1), 317–375. https://doi.org/10.5465/19416520903047327
25.
HackmanJ. R.OldhamG. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16(2), 250–279. https://doi.org/10.1016/0030-5073(76)90016-7
HumphreyS. E.NahrgangJ. D.MorgesonF. P. (2007). Integrating motivational, social, and contextual work design features: A meta-analytic summary and theoretical extension of the work design literature. Journal of Applied Psychology, 92(5), 1332–1356. https://doi.org/10.1037/0021-9010.92.5.1332
28.
JasanoffS. (2015). Future imperfect: Science, technology, and the imaginations of modernity. In JasanoffS.KimS.-H. (Eds.), Dreamscapes of modernity: Sociotechnical imaginaries and the fabrication of power (pp. 1–33). University of Chicago Press.
29.
KronemyerB. (2025a). The two big myths about using AI in healthcare. Healthcare Executive, March–April 2025.
30.
KronemyerB. (2025b). Improving patient care and safety with AI. Healthcare Executive, March–April 2025.
LatourB. (1992). Where are the missing masses? The sociology of a few mundane artifacts. In BijkerW. E.LawJ. (Eds.), Shaping technology/building society: Studies in sociotechnical change (pp. 225–258). MIT Press.
33.
LeonardiP. M. (2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies. MIS Quarterly, 35(1), 147–167. https://doi.org/10.2307/23043493
34.
LitwinA. S. (2022). Technological change and frontline care delivery work: Toward the quadruple aim. Advances in Health Care Management, 20, 99–142. https://doi.org/10.1108/S1474-823120210000020005
35.
MacKenzieD.WajcmanJ. (Eds.). (1999). The social shaping of technology (2nd ed.). Open University Press.
36.
MenchikD. A. (2020). Moving from adoption to use: Physicians’ mixed commitments in deciding to use robotic technologies. Work and Occupations, 47(3), 314–347. https://doi.org/10.1177/0730888420919792
37.
MorgesonF. P.HumphreyS. E. (2006). The work design questionnaire (WDQ): Developing and validating a comprehensive measure for assessing job design and the nature of work. Journal of Applied Psychology, 91(6), 1321–1339. https://doi.org/10.1037/0021-9010.91.6.1321
OldhamG. R.HackmanJ. R. (2010). Not what it was and not what it will be: The future of job design research. Journal of Organizational Behavior, 31(2–3), 463–479. https://doi.org/10.1002/job.678
40.
OrlikowskiW. J. (1992). The duality of technology: Rethinking the concept of technology in organizations. Organization Science, 3(3), 398–427. https://doi.org/10.1287/orsc.3.3.398
41.
OrlikowskiW. J. (2000). Using technology and constituting structures: A practice lens for studying technology in organizations. Organization Science, 11(4), 404–428. https://doi.org/10.1287/orsc.11.4.404.14600
OrlikowskiW. J.ScottS. V. (2016). Digital work: A research agenda. In CzarniawskaB. (Ed.), A research agenda for management and organization studies (pp. 88–96). Edward Elgar Publishing.
PasqualeF. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.
46.
PollockN.WilliamsR. (2009). Software and organisations: The biography of the enterprise-wide system. Routledge.
47.
RotensteinL. S.TorreM.RamosM. A.RosalesR. C.GuilleC.SenS.MataD. A. (2018). Prevalence of burnout among physicians: A systematic review. JAMA, 320(11), 1131–1150. https://doi.org/10.1001/jama.2018.12777
48.
SinskyC.ColliganL.LiL.PrgometM.ReynoldsS.GoedersL.WestbrookJ. I.TuttyM.BlikeG. (2016). Allocation of physician time in ambulatory practice: A time and motion study in four specialties. Annals of Internal Medicine, 165(11), 753–760. https://doi.org/10.7326/M16-0961
49.
StarS. L.RuhlederK. (1996). Steps toward an ecology of infrastructure: Design and access for large information spaces. Information Systems Research, 7(1), 111–134. https://doi.org/10.1287/isre.7.1.111
50.
StraussA. L.FagerhaughS.SuczekB.WienerC. (1985). Social organization of medical work. University of Chicago Press.
SuchmanL. A. (2007). Human–machine reconfigurations: Plans and situated actions (2nd ed.). Cambridge University Press.
53.
TimmermansS.BergM. (2003). The gold standard: The challenge of evidence-based medicine and standardization in health care. Temple University Press.
54.
TimmermansS.EpsteinS. (2010). A world of standards but not a standard world: Toward a sociology of standards and standardization. Annual Review of Sociology, 36, 69–89. https://doi.org/10.1146/annurev.soc.012809.102629
55.
TopolE. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.
56.
TristE. L.BamforthK. W. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations, 4(1), 3–38. https://doi.org/10.1177/001872675100400101
57.
VermeerbergenL.McDermottA. M.BendersJ. (2021). Managers shaping the service triangle: Navigating resident and worker interests through work design in nursing homes. Work and Occupations, 48(1), 70–98. https://doi.org/10.1177/0730888420930770
58.
WiednerR.NigamA.da SilvaJ. B. (2020). General practitioners are from Mars, administrators are from Venus: The role of misaligned occupational dispositions in inhibiting mandated role change. Work and Occupations, 47(3), 348–377. https://doi.org/10.1177/0730888420918643
59.
WinslowC. (2026). Kaiser Permanente, AI, and the Workers on Strike, Again. Counterpunch (March 23).
60.
WoolgarS. (1991). Configuring the user: The case of usability trials. In LawJ. (Ed.), A sociology of monsters: Essays on power, technology and domination (pp. 58–99). Routledge.
61.
ZuboffS. (1988). In the age of the smart machine: The future of work and power. Basic Books.
