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Strategies For Success: How Businesses Can Maximise ROI On AI In Project Management

generative artificial intelligence

As project management capabilities evolve and businesses seek new tools to optimise their operations, artificial intelligence (AI) is no longer a distant concept but a tangible tool available to organisations and capable of reshaping how teams operate.

While AI has many uses, it can be easy to get lost in all the features this technology can provide. However, if used effectively, AI technologies can usher in a new era of efficiency and productivity, enabling project managers to delegate tasks and focus on strategic decision-making.

However, even though the benefits of AI in project management are significant, they are not without challenges. To truly capitalise on AI investments, businesses must adopt a holistic approach that prioritises employee training, robust security protocols, and realistic outcome management. This article delves into these strategies, offering four key steps to help organisations enhance their AI-driven project management efforts and maximise ROI.

#1 Capitalise on growing confidence in AI-driven project management

The integration of AI into project management is transforming how tasks are executed, with a recent Capterra survey showing that 83% of project managers in the UK are comfortable delegating tasks to AI.

This confidence can stem from the proven efficiency of AI tools in handling routine and complex tasks alike. For instance, AI can automate repetitive activities such as data entry and status updates, freeing up valuable time for project managers to focus on more strategic responsibilities. The delegation of such tasks to AI has been shown to significantly enhance productivity, with 92% of project managers reporting a positive return on their AI investments.

Moreover, AI’s role in predictive analytics and forecasting is becoming increasingly vital. By analysing historical data and trends, AI can predict project outcomes, enabling managers to make informed decisions and mitigate potential risks before they escalate. This proactive approach not only streamlines operations but also builds confidence in the technology, as demonstrated by the fact that nearly 90% of project management professionals feel assured in leading AI implementation projects.

#2 Prioritise in-depth employee training

Despite AI’s benefits, the successful deployment of these technologies hinges on the human element—specifically, the training of employees. A significant portion of the challenges associated with AI in project management stems from a lack of understanding and proper usage of these tools. Identifying the time and effort required for employees to learn and effectively use AI tools can be a major hurdle.

To overcome this, businesses must prioritise in-depth training programs that cover both the technical aspects of AI tools and their practical applications in project management. Nearly half (49%) of surveyed project managers said that training on AI capabilities and limitations was the most helpful tool in mitigating challenges with AI in project management.

Training should not be a one-time event but an ongoing process that evolves with the technology. Workshops, hands-on sessions, and continuous learning platforms can equip employees with the skills needed to leverage AI effectively. Additionally, feedback mechanisms should be established to gather insights from users, enabling organisations to refine their training programs and address any pain points.

Investing in comprehensive training not only enhances the ROI of AI tools but also empowers employees to use these technologies with confidence. As project managers become more proficient in using AI, they can delegate tasks more effectively, optimise resource allocation, and ultimately drive better project outcomes.

#3 Develop robust security protocols to protect data

As AI becomes more integrated into project management, the issue of data security cannot be overstated. AI systems often handle sensitive company information, making them prime targets for cyber threats. According to Capterra’s survey, 35% of project managers that use AI cite security concerns as a significant challenge when using AI-enabled software.

To mitigate these risks, businesses must develop and implement robust security protocols. This begins with data encryption, which ensures that sensitive information is protected from unauthorised access. Encryption should be complemented by strict access controls, ensuring that only authorised personnel can interact with sensitive data. Furthermore, regular audits and security assessments are essential to identify vulnerabilities and proactively address potential threats.

Compliance with data protection regulations, such as the UK-GDPR, is also crucial. Organisations must ensure that their AI systems adhere to these standards, not only to avoid legal repercussions but also to build trust with stakeholders. Adhering to data classification policies, which dictate how data is handled and processed, further minimises the risk of exposing confidential information.

By prioritising security, businesses and project managers can safeguard their investments and ensure that AI tools contribute positively to their operations without compromising sensitive information.

#4 Maintain realistic expectations for AI outcomes

While AI offers remarkable potential, it is crucial for businesses to maintain realistic expectations about what these technologies can achieve. AI is not a panacea; it is a tool that, when used correctly, can enhance project management processes. However, overreliance on AI or unrealistic expectations can lead to disappointment and underperformance.

Nearly half of the surveyed project managers express some level of scepticism about AI. This scepticism is not entirely unfounded, as 91% acknowledge the limitations of AI in project management. For instance, AI’s effectiveness is heavily dependent on the quality of the data it processes.

Poor data quality can lead to inaccurate predictions, flawed analyses, and suboptimal decisions. Moreover, while AI can excel at automating routine tasks and analysing large datasets, it may not be as effective in areas requiring nuanced judgment or creative problem-solving.

To avoid such pitfalls, project managers must:

  • Set clear and realistic goals for AI implementation.
  • Understand the specific capabilities of AI tools and aligning them with the organisation’s objectives.
  • Foster a culture of collaboration between AI and human teams.

AI should be seen as a complement to human expertise, not a replacement. By clearly defining the roles of AI and human team members, organisations can enhance the quality of inputs and build trust in AI-driven processes. Regular check-ins and open discussions about AI’s performance and limitations can also help manage expectations and ensure that the technology is used to its full potential.

If used adeptly, businesses can harness the full potential of AI in project management

The rapid advancements in AI technology present a significant opportunity for project managers to enhance efficiency, productivity, and overall project outcomes. However, realising AI’s full potential requires a strategic approach that goes beyond mere implementation. By prioritising in-depth training for all employees, developing robust security protocols, and maintaining realistic expectations, businesses can maximise the ROI of their AI investments and mitigate associated risks.

Just as AI continues to evolve, project managers must remain agile, continuously adapting to new developments and refining their strategies. By doing so, they can harness AI’s transformative capabilities, driving technological innovation and achieving sustained success in an increasingly competitive landscape.

Eduardo Garcia Rodriguez is a content analyst at Capterra, covering research on new technologies across various industries. He has previously worked in corporate communication at the European Investment Bank and the World Organisation for Animal Health.

Eduardo also has a decade of experience in the private sector, communicating about topics such as artificial intelligence, smart cities, advanced analytics, and big data. His research has appeared in The Times, Vogue Business, Wired UK, Tech Radar, Customer Experience Magazine, the NHS and Computer Weekly.

Eduardo Garcia Rodriguez
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