COVER STORY – AGE OF AI
report states. “AI applications already exist that are applicable for every step of the development and engineering cycle from intelligence through to commercialisation. Prioritisation involves making diff icult trade-off s between what’s important versus urgent, what’s easy/low impact versus diff icult/high impact, and what’s no- regret versus speculative.”
TRENDS AND CHALLENGES According to the report, there are several key trends and challenges that are radically changing the nature of development and engineering. The fi rst challenge is what ADL refers to as demand-side challenges – increasing complexity, stricter compliance requirements, and a shift toward integrated, technology- rich solutions as consumers demand smarter, more personalised products. On the supply side, the report identifi es skill shortages in AI and software engineering, poor data quality and persistent supply chain disruptions as hindrances to companies’ abilities to innovate. From a trends perspective, ADL
predicts new capabilities in knowledge integration, data management and collaborative innovations will be essential to meet rising technological and regulatory demands. As a “transformative enabler”, AI can augment engineering capabilities, streamline workfl ows and drive innovation in order to address the growing demands of modern engineering. The report states: “Traditional
approaches are inadequate, adopting AI and other advanced methods is critical to overcoming challenges and maintaining competitiveness.”
PEOPLE BEFORE TECHNOLOGY Next, the report looked at the potential of current AI tools and the existing barriers to faster adoption, stating: “AI clearly emerges as the technology with the highest potential to transform engineering. Recent developments in AI give it the potential to enhance capabilities across tasks such as design, planning, and problem solving.” A lack of skills and data, lack
of trust and impact of regulations are some of the perceived risks
Source: Arthur D. Little Prioritisation by considering impact and adoption
of deploying AI in engineering and development according to the companies surveyed for the report. ADL also cites user attitudes and behaviours as potential barriers to the technology’s adoption, meaning a people-centric approach is crucial. “If we look at the future challenges
of development and engineering, the potential of AI to help address these challenges, and the risks and barriers around eff ective integration, we see that, more often than not, the issues are about people – engineers and innovators – rather than systems or technologies,” the report states. “If people are so essential to making progress in AI-enhanced engineering and innovation, it follows that the approach for integrating AI should be similarly people-focused.”
CAPTURING THE FULL VALUE The report concludes by outlining a practical approach to ensure the alignment of AI integration with the broader development and engineering technology portfolio, which ADL says is vital to ensuring that AI is being deployed to its full value. The report
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states that a strategic approach is key: “It is important to prioritise potential AI investments, aiming for competitive advantage to key user personas and their specifi c needs.” However, this is a balancing act: “Properly integrating various priorities requires a careful collaboration of the desired target situation – where should we aim high and where are incremental improvements good enough?” Therefore, an integrated roadmap
is needed: “A successful way forward aligns with the broader technology strategy, considers leading-edge AI developments and those that are more mature, and allocates implementation priorities based on impact, adoption, and return on investment (ROI).
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