Industrial AI: Transforming Economic Hubs Towards Diversification and Autonomy

As we navigate the fourth industrial revolution, the integration of artificial intelligence (AI) in industrial processes is proving to be both a challenge and an opportunity. In recent years, the conversation around AI has shifted from speculative to practical, particularly in the industrial sector. From small business owners managing purchasing, supply chain, staffing, and scheduling, to the leadership of multi-billion-dollar operations, everyone can now envision numerous applications for AI in their operations. Regional governments have been at the forefront of this conversation, accelerating the pace of AI adoption.

The Middle East has emerged as one of the global leaders in harnessing the potential of artificial intelligence, with Saudi Arabia and the UAE spearheading national strategies to integrate AI into their economic frameworks. Both nations have made substantial investments in AI as part of their broader vision to advance digital economies and drive economic diversification. By prioritizing AI, they aim to reduce reliance on traditional revenue sources, paving the way for sustainable economic growth. These strategies are not solely focused on technology but also emphasize talent development, fostering a highly skilled workforce, and attracting global expertise to ensure the region remains competitive in an increasingly digital world.

Recent Honeywell research shows decision-makers in the industrial AI space are dealing with a combination of well-placed enthusiasm coupled with some degree of uncertainty. The research report titled “A Pivotal Moment for Industrial AI” highlights the transformative potential of AI in industrial operations and the critical decisions companies must make to harness this potential.

The report highlights that the so-called AI revolution is, in fact, an evolution. Over the past few decades, control science has advanced from basic process control to plant-wide optimization, and now to the application of AI for predictive maintenance and operational efficiency. This progression has brought us to a pivotal moment, akin to the creation of ARPANET in the late 1960s, which eventually evolved into the internet. Today, industrial AI stands at a similar inflection point, with its potential limited only by our imagination and decision-making.

The research, which surveyed 1,600 industrial AI leaders across 12 global markets, reveals a landscape of both enthusiasm and uncertainty. A significant 82% of respondents consider their companies to be pioneers or early adopters of AI. Despite concerns about the understanding of AI at the C-suite level, an overwhelming 94% believe their organizations will continue or expand AI use in the coming years. This optimism is driven by direct experience, with 91% of respondents discovering new AI use cases during implementation. Notably, 97% of companies in the UAE found use cases for AI that were not in their initial plans, highlighting the region’s innovative approach.

Benefits and Challenges of AI Integration

The benefits of AI in industrial settings are widespread. Increased efficiency through automation, improved cybersecurity, and enhanced decision-making through real-time data are among the top advantages cited by AI leaders. Additionally, 39% of respondents report or anticipate improvements in worker safety. In the UAE, 49% of workers see more time for skill development as the biggest benefit, while in Saudi Arabia, 53% see AI complementing the workforce by improving efficiency and productivity. However, the journey to full AI integration is not without its challenges.

Nearly half of the respondents (48%) face ongoing struggles to secure sufficient resources for AI implementation, and two-thirds (63%) report that a significant portion of their equipment is not AI-compatible.

The Autonomous Maturity Model

To navigate the path to autonomy through AI, industries will need to take an iterative approach that encompasses data, design, and people. Data is the lifeblood of AI and leveraging it effectively can unlock significant operational improvements. For example, in oil refining, real-time data collection and analysis can bring endless opportunities to optimize performance and profitability.

Designing for AI integration is equally crucial. While many companies plan to replace non-AI-compatible equipment, AI can also be integrated into existing systems through strategies such as AI-powered sensors and cameras. Effective design also involves addressing common implementation challenges, such as budget overruns and inadequate training. C-suite respondents in the survey highlighted the importance of project oversight, increased AI budgets, and formal communication processes to ensure smoother implementation.

The Human Element in AI

Significant labor shortages are constraining productivity, especially in manufacturing, where nearly 75% of executives cite attracting and retaining a quality workforce as their primary business challenge. The energy industry faces similar challenges: the oil and gas energy sector is projected to experience a shortage of up to 40,000 competent workers by 2025. This is compounded by the fact that 62% of younger generations find a career in the field broadly unappealing. Over a third of employees are over 50 years old, and only 12% are under 30, making it difficult to replace retiring experts quickly enough with younger workers.

With a growing skills gap and the retirement of the baby boom generation, AI is seen as a tool to enhance worker efficiency and productivity. Contrary to fears of job displacement, AI can be used to increase worker flexibility, job satisfaction, and opportunities for skills development. In the UAE, 78% of companies expect to pay more to attract AI engineers, while in KSA, this figure is 80%. These statistics highlight the pressing need for investment in training and resources to bridge the skills gap and show that AI can be effectively integrated into the workforce, helping to enhance productivity and job satisfaction across industries.

Navigating the Future of Industrial AI

For industrial businesses on the path to autonomy, the critical components are data, design, and people. The potential for productivity and efficiency savings through AI-enabled automation is significant. However, successfully integrating these technologies requires carefully planned risk management strategies. When executed effectively, companies can unlock the immense potential of industrial AI and create new growth opportunities.

Read more here: “A Pivotal Moment for Industrial AI”

This article is adapted from a story originally published in Gulf Business in 2025.