Emerging Trends in Project Management and IT Delivery
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The document discusses emerging trends in project management and IT delivery, emphasizing the increasing influence of artificial intelligence (AI), automation, and a focus on soft skills. It predicts that by 2030, AI will manage 80% of project management tasks, transforming the role of project managers and necessitating adaptability to new technologies. While there are concerns about job displacement due to AI, there is an optimistic view that it will enhance productivity and efficiency, creating new opportunities.
Emerging Trends in Project Management and IT Delivery
- 1. Trends in Project Management and IT Delivery November 2024 Paul Gerlich Recently retired from TD Bank after an extensive and rewarding career in project management and IT delivery, most recently in the role of a release train engineer. Presentation: • Navigating the AI revolution – AI continues to reshape all industries with PM and IT delivery being no exception • Emerging Trends in PM and IT delivery
- 2. 1. Increased impact of Artificial Intelligence, Machine Learning, Generative AI 2. Automation of routine tasks 3. Increased focus on people – Soft Skills, Emotional Intelligence 4. Hybrid Project Management (hybrid teams, methodologies – Agile/Waterfall/other) 5. Implementing strong cybersecurity measures 6. Human/machine collaboration 7. Remote work access, virtual work teams – remote and hybrid work culture 8. Sustainability 9. Cloud Computing Trends and New Frontiers:
- 3. Impacts of Artificial Intelligence on Project Delivery Future AI tools developed to support project management will result in radical changes how projects and IT systems are delivered. Gartner’s research predicts that by 2030, 80% of PM tasks will be run by AI, powered by big data, machine learning (ML), and natural language processing. Important areas where AI will be used to support PM and delivery leads: • Virtual Assistants Applications and tools helping to automate administrative and supporting tasks with the help of AI technologies, including natural language processing, voice recognition, machine learning, voice recognition. Assistants will be able to suggest plan adjustments and corrections. • Virtual Advisors • Data Analytics Tools and algorithms to structure , organize and analyze large amounts of project related data • Improved Performance Metrics and Monitoring Enhanced progress reporting, suggestions for plan adjustments, earlier detection of risks • Analysis of User Stories AI tools that could analyze user stories, uncover inconsistencies, ambiguity and redundancy. • Analysis and highlighting potential problems, automatically self-correcting simpler issues • Regulatory and compliance monitoring • Selecting the right projects, define them correctly and assist in implementing them successfully • AI-Powered tools non-specific for PM For example: AI tools for test automation, workflow monitoring, collaboration, setting up chatbots for common queries, reporting, documentation, meeting agendas and minutes, scheduling, analytics, financial management, scheduling assistants etc. Organizations believe that the main roles of AI would be as PM assistant (52%), PM advisor (42%), and PM substitute (3%) (IPMA, 2020)
- 4. Impacts of Artificial Intelligence on Project Delivery How will AI impact the PM profession? • Project Managers will need to demonstrate readiness to learn and adapt, to explore and embrace new technology • Project Managers may no longer have the PM title but there will continue to be a role for managing delivery of products, features, technology components, software releases etc. • Project Managers will need to understand and utilize data analytics • Project Managers will need to rely heavily on automations • Organization ability will be the main success factor The future of project management remains bright for the foreseeable future. There remains strong demand for people delivering change. Global demand for project manager role has been increasing. PMI says that by 2027 employers will need nearly 88 million people in project-related roles. According to the Standish Group, only 35% of projects are considered successful. If applying AI and other technological innovations to project management could improve the success ratio of projects by just 25%, it would equate to trillions of dollars of value and benefits to organizations, societies, and individuals.
- 5. Impacts of Artificial Intelligence on Project Delivery Questions about future – predictions: • Pessimistic Views: Fear of loosing jobs that will be replaced by AI, causing political and social issues • Optimistic Predictions: AI will enable automation of mundane tasks, increase productivity, efficiency, reduce costs, while new jobs and opportunities will be created • Middle Ground: Ability to adapt is the key, just like it was historically during industrial revolution, advances in communication, computerization, internet proliferation, robotics, globalization etc. AI is not replacing human minds. Admittedly, rate of new AI-related job creation will likely not be keeping up with jobs replaced by AI. In future project, cross-functional teams may include both humans and machines, while machine will not fully replace people
- 6. Impacts of Artificial Intelligence on Project Delivery Ethical Concerns and Mitigation AI is a powerful tool and we need to ensure it is used for public benefit, that is not misused for malicious purposed, that it is safe, secure and trustworthy. • AI can provide wrong answers • Bias mitigation, prevention of discrimination – AI provides answers based what humankind created, often with human biases, offensive language etc. * • Risk management, thorough testing, built-in controls and built-in inherent values must be part of project planning for any successful AI implementation • Responsible AI development - guiding principles need to be established and followed to ensure AI is developed and used responsibly • Preventing Malicious Intents: Abusive AI generated content, cyberthreats with unique AI risks, privacy invasion, misinformation deepfake audio and video content • Robust protection mechanism, practices and tools need to be implemented • Many large companies started implementing frameworks and standards for AI systems, which includes behavioural guardrails, measurements, self-reflective systems etc. Leadership oversight is needed with a capacity for urgent corrective actions. * In 2016, Microsoft’s chatbot Tay started tweeting highly offensive comments and had to be shut down within 24 hours of the launch, after a coordinated attack exploiting vulnerabilities in Tay.
- 7. Automation of Routine and Repetitive Tasks Routine, repetitive and simple tasks related to project management will be increasingly automated. Automation has been used already in the following areas, and use of automation will be expanding. • Status/Progress Reports Including real-time report preparation, distribution and processing feedback • Risk Assessments Using AI to analyze large amounts of historical data and interpret the data to highlight risks that may not be obvious to project teams. These tools can also recommend mitigation strategies. • Stakeholder Analysis Stakeholder identification, analysis of relationships and influence, devise engagement strategy • Automated Testing Advanced testing tools will be able to access extensive libraries of earlier test cases, will facilitate set up of complex, accurate and rigorous testing processes. Objective of these tools is an earlier detection of problems, reduction in time spent on set up, and rework reduction. Advanced tools will increasingly incorporate self-correcting elements. Data processing tasks and reporting will be automated first, followed by some activities that require reasoning and decision making. The latter activities will not be fully automated in the near future. Automation of a large number of tasks currently handled by project managers will initially cause concerns. However, successful PMs will learn how to use the available tools to their advantage.
- 8. Increased Focus on People – Soft Skills, Emotional Intelligence Role of a project manager is changing with automation of routine and administrative tasks to focus increasingly on human interactions. Soft skills and leadership qualities will become more important, with specific emphasis on: • Communication • Problem-solving • Collaborative Leadership • Strategic Thinking • Adaptability • Business Acumen • Emotional Intelligence PM training, certifications and college education will need to adjust to the changing role of PMs.
- 9. Hybrid Project Management Collaboration between organizations, or parts of the same organization using different project methodologies, such as Agile, Waterfall and Scaled Agile will require project managers to work in environment using hybrid processes. AI tools can actually help with selecting the best methodology for a specific project. Scaled Agile (SAFe) is a framework based on core competencies of business agility. SAFe requires the entire enterprise to embrace the principles and partice of Lean and Agile. This is different from applying Agile practices by smaller teams on smaller projects in the past. Design Thinking – creating customer centric products, aligning with customer needs and requirements. Emphasis is on customer value and satisfaction. Products are designed and developed in iterations with continuous refinements through frequent customer feedback. This results in reduced redesign, less rework and better risk mitigation. Note about “Agility Trap”: Agility, or quick reaction to business environment changes, has been highlighted as important aspect for enterprises to succeed. However, constant shifts can result in too many projects, too much diversification, endless changes in direction and too many moving targets. Recently, calls were made to embrace “strategic constancy”. While agility is a sound objective, certain strategies should not change too frequently. * * Jeff Bezos, the founder of Amazon, once made an interesting observation: “I very frequently get the question: ‘What’s going to change in the next 10 years?’… I almost never get the question: ‘What’s not going to change in the next 10 years?’ And I submit to you that that second question is actually the more important of the two—because you can build a business strategy around the things that are stable in time.” – Harvard Business Review, How to Avoid the Agility Trap (Jianwen Liao and Feng Zhu)
- 10. Cybersecurity Measures Implementing strong cybersecurity measures will become increasingly critical. • Protection from ransomware • Cloud security • Protection from social engineering • Improved multifactor authentication • Growing importance of Internet of Things security • Rise of Quantum Computing – security protocols may become unsafe in the world of quantum computing … emergence of cloud computing will require a new level of protection Cost of cybercrime globally is projected to increase at an alarming rate – from $8.44 trillion in 2022 to a shocking $23.84 trillion by 2027.
- 11. Human/machine collaboration With machines taking on roles that were held by humans in the past, we will need to shift our thinking to consider AI tools and machines to be part of the project teams for specific roles. Preparing an organization for adoptions of new AI tools requires not only data science and training AI models; preparing people within the organization is just as critical. How do we ensure people are ready to use the new AI tools? … training, involvement in design, development, testing, deployment
- 12. Trends in Project Management and IT Delivery Effective communication across geographical distances, time zones, cultures, language barriers needs to be facilitated. Remote work access, virtual work teams – remote and hybrid work culture Balancing project benefits and needs of key stakeholders in a transparent, fair and ethical way, while avoiding liabilities for society, and burdens for future generations. Innovation and stakeholder management are key for PMs to achieve sustainability objectives. Sustainability Not a new trend – adoption of on-demand cloud computing services will continue, as demands for scalable flexible platforms will increase with development and implementation of AI tools. Cloud Computing