Advances in AI will continue to bring promise and challenges to the manufacturing industry
LightRocket via Getty Images
You've probably heard a lot of talk about artificial intelligence (AI) lately, but the truth is that AI is not new: As early as the 1950s, AI helped create basic problem-solving models, and with every decade since, the length and breadth of its use cases has steadily increased.
What's new, of course, is the speed at which AI capabilities have exploded in recent years: Generative AI is enabling increasingly sophisticated applications to carry out tasks that once took humans hours or even days to complete within minutes.
While this rapid progress has been impressive, the real driving force behind AI is not AI itself, but the technologies that support and enable it. Just as the problem-solving model of the 1950s could not have worked without large computer mainframes, today's AI would not exist without recent advances in mobile phone technology, the cloud, and high-density data storage.
As EY technology strategist Sook Chua recently put it, “AI builds on emerging technologies and infrastructure, not the other way around.”
Exciting but still limited
Therefore, manufacturers must resist the temptation to get swept up in the hype surrounding AI and focus on how it can be used to solve real business challenges, now and in the future.
There are already many use cases to choose from, most of which are focused on improving the productivity of human workers – including everything from automating inventory management to smarter logistics planning to facilitating improved communication and data sharing between companies and suppliers.
Many businesses are also turning to AI for content creation, producing text, video, and graphics faster and more cost-effectively than ever before. For example, imagine that having an AI create multilingual standard operating procedures is much more efficient than having a team of employees spend days creating and translating them.
While excited by the potential of AI, the industry should also focus on what AI cannot do: make recommendations or decisions. For example, on a manufacturing floor, AI may be able to pinpoint unsafe working conditions or suboptimal processes, but it still can't think critically about how to solve them.
Committee Decision
Manufacturers have a two-fold task ahead of them: First, they need to understand the possibilities and limitations of AI and be ready to take advantage of modern applications today, but at the same time, they need to plan and be ready for what comes next.
This is a considerable challenge, so rather than relying on a single chief information officer or chief technology officer to tackle the problem, companies should establish a governance committee to act as stewards of the organization's entire technology ecosystem, including the responsible development and deployment of AI.
Reporting to the CEO and interacting regularly with the board, this committee should be truly multidisciplinary, ideally consisting of representatives from HR, legal, marketing, finance and technology (data, cyber, infrastructure and IT risk).
Importantly, they must recognize their responsibility goes beyond the application of AI and take the lead to ensure all technology investments are aligned with the organization's overall business priorities and goals.
This involves continually monitoring and evolving their strategy in line with advances in the technology infrastructure itself. After all, Sook Chua explains, “the more tools we have available, the faster we can move to the next stage of AI.”
Now and in the future
Predicting exactly what this next step will look like can be difficult given the rapidity of recent advances, but already developments in areas such as quantum computing and causal or explanation-based AI are improving the speed and accuracy of training AI models, offering glimpses of a world in which AI reasons and interacts in more human-like ways.
Moreover, while there may still be uncertainty about what the future of AI will hold, one thing is certain: AI capabilities will never be as limited or inadequate as they are today. The AI era offers manufacturers a future of nearly limitless possibilities, but only if they have the technological infrastructure ready to unleash them.
The views reflected in this article are those of the author and do not necessarily reflect the views of Ernst & Young LLP or other members of the EY global organization.
###
