Comment: AI and its impact on the engineering industry

Engineering is an industry that sits at the cutting edge of technology. Regularly going above and beyond expectations and challenging boundaries, the industry is familiar with innovation – in fact, it is a fundamental part of the sector. It’s likely why the theme of this year’s Engineer’s Week is ‘Welcome to the Future’, showcasing the successes of firms and raising awareness of innovations to date, recently driven by the adoption of Artificial Intelligence (AI).

While adoption of AI for many is still within the early stages, there is a huge opportunity for engineering firms.

AI in engineering: State of adoption

While the buzz around AI appeared in the media landscape last year, the technology has been leveraged within the engineering field for decades. For example, on sites, predictive maintenance is regularly used to monitor equipment and prevent failures before they happen – powered by AI. In fact, our research reveals that even in early in 2023, 86 per cent of engineers valued AI as an important emerging technology.

When we say AI, it’s important to remember that the term serves as an umbrella, encompassing techniques that empower machines to perceive reasons, learn and make decisions. Within the vast umbrella, there are then subsets like machine learning (ML), deep learning and of course, generative AI, such as ChatGPT. Together, the technology holds the potential to redefine the project lifecycle even further, specifically looking at project efficiencies.

Opportunities for change

Despite the engineering sectors appetite for innovation, the back-office side of engineering is still heavily reliant on manual processes.

Take project reporting planning as an example. When a contract is signed, the project manager is tasked with creating a project plan. That project plan needs to take into consideration the objectives, scope, resources, schedule, risks, dependencies, and tasks to name a few points. It is a complicated process that takes a significant amount of time; however, ML can streamline the process by analysing past project behaviour and performance data, making recommendations on how to build the new project plan – while suggesting operational efficiencies on everything from timelines to resourcing. Put simply, ML enables machines to learn from data without explicit programming. Statistical techniques drive learning, allowing machines to automatically detect patterns and make predictions.

Leveraging these insights, AI can aid in the decision-making process. By analysing historical performance and data inputs, business leaders can make decisions based on data, in turn supporting the stability and growth opportunities for the firm. For example, if a big project is going through uncertainty, leaders can request insights in moments to make real-time planning and resource changes, instead of wasting time and resource for insights to be collected manually.

Embracing AI, purposefully

While adoption of AI across the engineering industry is constantly growing, the opportunities remain endless. The key to unlocking profitability leveraging AI is focusing on the areas of business where efficiencies can be made – rather than where ‘world-firsts’ can be claimed. For example, improving how the firm operates through automation, more informed decision making and exploiting data and analytics.

One purposeful application of AI is more efficient harvesting of information and insights. With clients at the heart of every project, having a thorough understanding of a client’s history, ongoing projects and potential opportunities is crucial to fostering meaningful conversations. These conversations can be the difference between a project win or loss. The problem is, when you have dozens of clients, remembering and accessing the insights needed can be incredibly time-consuming and overwhelming. This is where purposeful innovation comes into play.

Through the application of generative and traditional AI, firms can proactively harvest client insights. Through a quick and simple natural language interaction, project managers can have detailed client overview documents available in an instant, without running a report or asking someone else to retrieve the information. These client insights arm project managers to build and enhance vital relationships, while reducing the resource impact on the business. A prime example of how engineering companies can combine human and artificial intelligence to generate the biggest business impact.

For too long as an industry, we’ve been reliant on manual data entry and in turn, lost critical business insights. In 2024, this has to change. Fears around AI taking employees jobs need to be dispelled and engineering companies must realise that AI will augment human capabilities, not replace them. Amid the talent shortage facing firms, AI-driven automation can alleviate workloads by reducing manual data entry, allowing firms to redeploy resources strategically.

While AI is a complex technology, simply put, the biggest opportunities are often the simplest deployments. As such, firms need to be proactively looking at their business and identifying the areas where the biggest impacts can be generated. Working with a project provider that not only embraces AI, but fundamentally deploys AI-driven solutions, aligned to project-based business challenges, is a simple and cost-effective way to make efficiencies, without investing significantly in emerging technology deployment.

Navigating the AI landscape in 2024

Investing in digital transformation has never been more important. Research shows that 84 per cent of engineering firms expect to lose market share within two years if they fail to make progress with digital transformation.  However, as we approach Engineer’s Week 2024, ‘The Future of Engineering’ looks positive. The market is recovering and the project pipeline filling up. As AI and ML reshape the industry, project leaders understand the need to evaluate and embrace the diverse capabilities of AI tools and take an active approach to implementation.

Adopting AI successfully, in a way that furthers business growth, requires a well-through-out change management plan and support for individuals adapting to technological shifts. In an environment when every project counts, maintaining pace with technology innovations has never been more important.

Bret Tushaus, vice president of product management, Deltek