Unfinished Products

Four decades back, Leonard-Barton and Kraus identified challenges faced by organizations while adopting novel technologies. A pertinent concern, given a 70% failure rate in organizational transformations (McKinsey, 2019) still happening nowadays.

Leonard-Barton and Kraus outlined six dimensions that, if overlooked, could sabotage technology implementation success: mastering separate skills for new technology development and implementation; catering to diverse stakeholders; rationalizing change; clarifying expected benefits; effectually introducing and scaling the technology; and ensuring accountable execution (Leonard-Barton, D. and Kraus, W., 1985).

Subsequent research has proposed new disciplines and practices to mitigate these implementation pitfalls.

Change management, addressing both engineering and human aspects, has emerged to navigate the dualism between technology development and implementation while accommodating the accelerating pace of business transformations (Hiatt J. & Creasey T., 2013).

Increased organizational complexity has spurred new approaches to technology delivery and architecture. Agile methodologies, deploying short iterations and continuous feedback, help handle complex technology needs (Sindhgatta R. & Narendra N. & Sengupta B., 2010). Distributed microservices architecture, along with modular systems, allows stakeholders to assume ownership and responsibility, while addressing broader enterprise considerations (Vaughn V., 2013).

In recognizing and managing technology hype, industry analysts provide critical insights into a technology’s actual business value, such as Gartner’s Hype Cycles (Gartner, 2023).

To ensure accountability in new technology implementations, the role of the Chief Technology Officer (CTO) has evolved. In technologically driven firms, the CTO extends from R&D delivery lead to managing innovations across the organization (Medcof J.W & Yousofpourfard H., 2006). Megan Smith, US CTO, for example provided a blueprint of how harmonizing technology advancement with constituent concerns (Vinton G. C., 2015).

However, despite improved disciplines, the complexity, scale, and dependencies of new technologies (Broekel T., 2019) pose continued challenges. Digital transformations, while offering opportunities for organizational reinvention, require managing changes across the entire organization (HBR, 2018). Digital transformations failure reasons such as implementation politics and lack of engagement persist (Forbes, 2022; HBR, 2018; Gurbaxani V. & Dunkle D., 2018), keeping Leonard-Barton and Kraus’s observations relevant.

Personal experience suggests that unclear vision, skill mismatches, politics, and personal agendas undermine even largely funded transformation projects.

Reflecting on public sector transformations, Kempeneer and Heylen (2023) argue that public entities shouldn’t pursue private sector goals like cost reduction but should focus on using technology to enhance fairness and impartiality.

If handling complexity and human psychology factors are key for successful technology implementation, exploring transformation management processes delivered by Artificial Intelligence Factories digital agents (Iansiti M. & Karim R. L., 2020) could be advantageous. This might seem futuristic, but studies show its relevance and feasibility in various fields (Bakke N. A. & Barland J., 2022; Jia P. & Stan C., 2021; Towson J., 2023). As a technology strategist, I find the digital agent model increasingly pertinent. Contexts of innovation, using Generative AI to simplify and support human factors in digital transformations, are being explored with customers. However, this model presents new ethical, authenticity, and human role concerns that need addressing.

Conclusions

Leonard-Barton and Kraus’s forty-year-old observations on how to successfully implement new technologies remain relevant today. Despite the industry’s concerted efforts to enhance disciplines and methodologies, the growing complexity and impact of technologies continue to offset these gains. With the advancement of Generative AI, a new approach based on a digital agent model presents a potentially efficient solution to master new technology implementation. However, it also raises existential challenges that were unforeseen forty years ago.

If handling complexity and human psychology factors are key for successful technology implementation, exploring transformation management processes delivered by #AIFactories #digitalagents could be advantageous.

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While the English fluency and syntax validation of this article has been validated by ChatGPT, the content authenticity is based on the critical reading and reflections of the author’s personal experience and the study of the references listed below.

List of References

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