How AI Improves Task Prioritisation and Delegation

Seemingly every week, companies in the wireless and telecommunications sector are having to navigate a whole range of complex project management changes. In the long run, the push from 5G to 6G, scaling and expanding sector-wide IoT deployment present milestones to strive towards. Simultaneously, as companies scale, they become busier, and their workloads increase exponentially.

Enter AI, a technology that’s been vastly covered, misunderstood and misused. A technology that serves to disrupt, but also, more importantly, to empower.

As resources dwindle and priorities change, tech leaders now face a dichotomy when it comes to AI. It’s a technology that underpins numerous new tools and applications that we use every day (from search engines like Google to customer service chatbots running through WhatsApp). However, it’s also reshaping how organisations determine what matters most to them, by reviewing what resource-heavy tasks and processes they can entrust to smart, deep-learning algorithms while they can continue to scale.

The Scale of the Challenge

The global AI in project management market was valued at $3,28 billion in 2024, and is expected to grow at a CAGR of 16% between 2025 and 2032 (to reach a valuation of $10.37 billion). This explosive growth reflects the trust and investment that leaders are putting in AI, and in a project management context, it illustrates how many companies are finding solace in it as a means of streamlining and simplifying many of their routine processes. It’s been said a million times already, but everyday project updates, tasks, reminders, data entry, and administration can now be adequately handled by AI tools, provided that there is adequate human supervision.

For wireless technology businesses managing everything from complex satellite communication projects to widespread 6G deployment to incumbent asset management solutions, AI tools can now analyse dozens of variables with accuracy. What’s more, these variables, such as resource quantity, task dependencies, urgency, and risk factors can be calculated in a fraction of the time that human managers would take to assess and conclude manually.

The Human Element

However, whilst AI excels at processing data and identifying patterns, successful delegation still requires human judgement. A technology organisation may discover that the combination of AI-led administration and task management with skilled, qualified human support creates the most tangible, measurable and effective outcomes.

As one business founder reflects on hiring support: "When I eventually started delegating, I went through all these options... I designed it to solve every single problem I'd encountered." This insight, from Time etc, underscores an evergreen discussion point for ambitious business leaders agnostic of sector: "What if hiring support is the very thing you need to get organised, instead of just getting through the day?"

For technology professionals overwhelmed by differing priorities and an abundance of tasks, this eloquent question should serve as a poignant reminder of AI’s place. AI can handle the analytical heavy lifting (processing data, evaluating insights, forecasting and predicting resource requirements), while internal or outsourced staff can oversee the human coordination efforts that technology cannot replicate.

Where’s the Proof That It Works?

The Project Management Institute believes that 80% of project management tasks will be AI-led by 2030.

The same research suggests that 82% of business leaders believe AI will transform project management profoundly within the next five years.

A 2024 study from Veritis reported that nearly 90% of telecom companies were using AI in some capacity, and 41% of these were in the process of moving to full-scale deployments.

AI-powered virtual assistants are believed, according to Sprinklr, to make query response times and issue resolutions 21 times and 50% faster, respectively.

Implementation Considerations

For Cambridge Wireless members evaluating the reasoning behind AI adoption, it’s prudent to pay attention to several factors.

AI systems require clean, structured data. Wireless companies must ensure all their incumbent applications, platforms and tools can support AI integration. Furthermore, given the sensitive nature of telco infrastructure, AI implementations must incorporate robust cybersecurity measures. Many AI-powered IoT security systems can now identify and prevent cyber threats in real-time, but access to this infrastructure should be carefully considered and budgeted for if feasible.

Fundamentally, it’s vital to establish clear policies and protocols for when AI recommendations require human validation. This will ensure long-term accuracy and validity with any AI-led outputs and data whilst maintaining the speed benefits automation provides.

Harnessing AI’s True Purpose

As 6G development accelerates, the complexity of wireless technology projects will only increase. AI will continue to become a mainstay in the scene, and harnessing it for its true inherent purpose (to support and augment people, as opposed to restrict and make them redundant) will position organisations more effectively for the long haul. Rethinking how you allocate resources and manage priorities now will give you the best possible chance of weathering the proverbial storm when AI becomes even more embedded within everyday business processes, outcomes and discourse.