How AI tools are helping managers enhance their project management efficiency and productivity

Project management is key for overseeing project life cycles but often needs to adapt to high operational demands. Artificial intelligence (AI) can be a transformative tool if used correctly. Merging AI with business technology like project management software can help companies enhance efficiency and productivity. Here are steps project managers can take to make sure AI is deployed effectively.

As important as it may be, emotional intelligence (EQ) is only part of the equation for optimising project management. Technology and automation also have huge roles to play in aiding project managers to do their job more effectively. Artificial intelligence (AI) promises great potential in transforming project management, offering opportunities to streamline processes and drive organisational success. In fact, according to Capterra’s recent survey, over half of project managers feel the most beneficial aspect of AI in project management is increased efficiency and productivity.

To evaluate the impact of AI on project management, Capterra surveyed 2,500 project management professionals across 12 countries.* We will focus on insights gleaned from 200 respondents from the UK to show how, alongside project management software, AI is a tool that can deliver positive ROI, and inspire confidence among project managers, but also requires training, monitoring, and security awareness.

Nine in ten project management professionals report a positive return on their AI investment in project management

Many companies are actively using AI technology in some way. With the emergence of large language models (LLM) and generative pre-trained transformers (GPT), which can generate content from scratch using patterns learned from large data models, many corporations are starting to implement generative AI into their operations. In fact, of our surveyed project managers, 57% say their company is using generative AI. In addition, 45% of companies are using AI software such as chatbots or sentiment analysis in their customer services.

When it comes to project management, 45% of surveyed project managers also use AI technology to help in this department with essential project management tasks like planning and scheduling.

For these companies deploying AI tools in project management, the investment is worth it. An overwhelming 92% report a positive return on their AI investment in project management. The satisfaction is such that 81% of respondents using this technology in project management anticipate AI investments in their organisation’s project management function to increase by between 10% and 50% by 2025.

While the general premise behind using AI is most likely to enhance productivity and support teams in automating repetitive tasks, enabling them to focus on strategic initiatives, there are multiple ways AI can be strategically used in project management.

Almost all project managers are comfortable delegating to AI, but sceptics remain

Leadership confidence can play a pivotal role in ensuring the success of AI implementation strategies. Assertive assurance in strategic decisions can inspire trust and commitment among teams, as well as foster effective collaboration and alignment with goals. With this in mind, 89% of project management professionals express confidence in their ability to lead AI-implementation projects.

Also, a majority (83%) of project managers are comfortable delegating important tasks to AI. This can be due to its efficiency in delivering certain tasks. Task automation (47%) predictive analytics (38%), and project planning (34%) are identified as the areas where project managers think AI can have the biggest impact on their work within the next 12 months.

However, despite the help artificial intelligence can provide to project managers, there is still some apprehension surrounding the technology. Nearly half (49%) of surveyed project managers disclose that they are sceptical about AI. However, some level of scepticism is warranted, given the possible challenges and limitations of the technology: 91% say they understand the limitations of AI in regard to project management.

Understanding AI's limitations can help managers use the tool more comfortably and confidently. Managers should keep this in mind and be prepared for any challenges that may arise.

Data quality and security issues are the biggest challenges for project managers using AI-enabled software in their company

Implementing AI technology in any area of a company’s operations isn’t without its challenges. According to our survey, 38% of organisations cite data quality issues as a primary challenge. Security and employee focused issues also feature as notable challenges when using AI software in business operations.

How can project managers address the key challenges in adopting AI software? 

Here are some steps project managers and senior managers can take to tackle the key challenges in AI-tech adoption.

1. Ensure accurate and reliable data: Data quality challenges pose significant hurdles for AI implementation in project management. Ensuring accurate and reliable data inputs is crucial for AI systems to generate meaningful insights and recommendations. Organisations facing data quality challenges should consider data governance frameworks, policies, and control measures to set standards for how data is collected and checked. 

2. Leverage data encryption, audits, and compliance to deliver data privacy and security: Addressing concerns about data privacy and security, highlighted by 35% of respondents, is paramount when leveraging AI technologies that handle sensitive company information. This can be done in several ways. For example, project managers can:

• Implement data encryption protocols to protect sensitive information from unauthorised access or breaches. 
• Ensure compliance with relevant data protection regulations like UK-GDPR [1] and industry standards in AI implementation.
• Deploy strict access controls and authentication mechanisms to limit access to sensitive data to authorised personnel only.
• Conduct regular audits and security assessments to identify vulnerabilities and proactively mitigate risks. 
• Adhere to data classification policies to ensure that only non-sensitive, permissible data is used in AI models, preventing the exposure of proprietary or confidential information.

3. Deliver training and feedback mechanisms to steepen the learning curve: A third of respondents noted that the time and effort required for employees to understand and effectively use AI tools was a challenge. Organisations can help employees in this facet by developing training programs and workshops that cover both the technical aspects of AI tools and practical applications in project management. This can be complemented with feedback mechanisms to gather insights from users about their experiences with AI tools and identify areas for improvement.

4. Use change management strategies, support, and intuitive interfaces to encourage employee adoption: With 32% of respondents highlighting employee adoption of AI technology as a challenge, project managers must address issues surrounding the readiness and willingness of staff to embrace AI. To overcome resistance and foster adoption, project managers can develop comprehensive change management strategies that involve clear communication about the benefits of AI. Additionally, user-friendly interfaces and providing ongoing training, support, and resources to address concerns can help employees integrate AI into daily operations.

AI can bolster project management operations but requires employee training, company policies, and team communication 

As AI becomes more prevalent in organizations, project managers should leverage its potential while addressing challenges such as data quality, biases, and accountability. This involves training teams on AI capabilities and limitations, setting realistic expectations, and defining clear roles for AI and human team members to enhance input quality and trust in AI.

Project managers should also foster open discussions about AI concerns and expectations among stakeholders and employees. Employing emotional intelligence, such as empathy, support and guidance,  and performing regular check-ins, can help address skepticism and build trust. By promoting a culture of continuous learning and adaptation, managers can better navigate AI implementation and achieve positive outcomes for the organization.