The global market for AI in the project management market is predicted to reach USD 2.93 billion in 2024 and USD 6.51 billion by 2029, growing at a CAGR of 17.3% during the forecast period.
Artificial intelligence (AI) is the simulation and modeling of human cognitive processes by computer systems that enable machines to emulate human intelligence. AI uses algorithms to examine enormous data sets to detect traits, classify kinds and learning preferences, and predict behavior.
Artificial Intelligence (AI) in project management can be considered a system introduced into the project management process to support humanitarian efforts. It uses the infinite processing power of machine learning to add meaning and assist with project-related decisions. AI’s primary function in project management is to bring value at various phases of the project lifecycle. AI can allocate and distribute resources and tasks, assist in matching the correct skills and allocating responsibilities to the right resources, and aid the hiring process by identifying the most qualified candidates for the project.
These tools and strategies have been developed over time and have demonstrated their efficacy in the management of business-wide projects. However, according to specialists in project management, only 35% of projects reach production and are effectively finished within budget, schedule, and plan. Inadequate resources, poor project planning and management, a lack of stakeholder participation and communication, and shifting project needs are the leading causes of project failure. Companies can deploy AI-based project management solutions that automate mundane tasks. Using AI in project management has the potential to substantially enhance project results, reduce expenses, boost efficiency, and cut costs. This is one of the major driving factors of AI in the project management market growth rate.
Cost Optimization- In today's competitive business world, organizations that want to improve their bottom line must focus on cost optimization. Project management is one where businesses can find big opportunities to cut costs. Using AI-based project management tools, companies can find ways to save money and improve the overall efficiency of their projects. AI-based project management tools can help organizations find ways to cut costs by analyzing project data from the past to find places where spending can be cut. AI can look at data on how resources are used and bought and how projects are scheduled to find inefficiencies and ways to save money. This can help businesses make better use of their resources, streamline their buying processes, and cut down on project delays, which can save them a huge amount of money. AI-based project management tools can do more than just cut costs. They can also improve the overall efficiency of a project. By automating continuing tasks like data entry and reporting, project teams can spend their time on tasks that add more value and lead to better project results. AI can also give organizations predictive analytics that helps them make data-based decisions. This can lead to more accurate project forecasts and better results overall.
Rising concerns regarding data privacy and security- Data is sometimes viewed as an organization’s most valued asset that demands cyber threat defense. When businesses adopt cutting-edge digital technology, they put their corporate data in danger. Regardless of how well prepared an organization is to combat cybercrimes, it will always struggle to overcome these threats. Every innovation that promises to improve business processes increases the number of points of entry for hackers and criminals into IT systems. This is the primary barrier stopping firms from implementing AI-based project management solutions. Affordable public cloud services are widely accessible to small and mid-sized organizations. However, these services are more susceptible to cyber-attacks and security difficulties, and small enterprises cannot afford a private cloud due to monetary constraints. In addition, the availability of project management tools on mobile devices increases their susceptibility to data breaches and cyber-attacks. Consequently, it is possible to conclude that organizations in highly regulated industries are hesitant to use cutting-edge AI-based project management systems due to cost constraints or information security concerns. Hence, the rise in concerns regarding data privacy is limiting the demand for AI in the project management market.
REPORT METRIC |
DETAILS |
Market Size Available |
2023 to 2029 |
Base Year |
2023 |
Forecast Period |
2024 to 2029 |
CAGR |
17.3% |
Segments Covered |
By Component, Application, Deployment Mode, Organization Size, End User, And Region |
Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
Market Leaders Profiled |
IBM, Oracle, Hitachi, Adobe, Microsoft, TIS, Service Now, Alice Technologies, Bubblz, Clear Strategy, Code Complete, Wrike, and others. |
Based on components, the AI-based project management market is categorized into solutions and services. Out of which, the predictive analysis of solutions is anticipated to be the largest market size over the forecast period. Many industries are employing predictive analytics to increase their profitability and competitiveness. Companies can utilize predictive analytics to evaluate variance and variation, refine predictions regularly, and monitor projections alongside historical performance. By making this forecasting data visible and accessible, service teams have the information they require when needed. This method can help businesses overcome a variety of problems. This involves keeping projects within their allocated budgets.
Based on application, the risk management segment will have the highest CAGR among all other applications over the forecast period. In project management, risk management refers to the process of identifying, assessing, and preventing or mitigating risks that have the potential to affect the desired outcomes. Normally, project managers are responsible for overseeing the risk management process throughout a particular project. Managers of projects must have a thorough understanding of their objectives to identify any impediments that could hinder the team’s ability to reach its objectives. This is essential for effective risk management.
The AI-based project management market is divided between cloud and on-premises based on deployment mode. Throughout the forecast period, the market size for the cloud deployment option is projected to expand quickly. Cloud computing has grown in popularity recently as internet connections have improved, and remote work has become more prevalent. Companies are constructing international teams to improve their project deliverables. Traditional software installation and maintenance might be tough for a decentralized team, but with cloud-based software, anyone can remotely access the solution.
The AI-based project management market is split into two parts: large enterprises and small and medium-sized enterprises. SMEs are expected to grow at the fastest rate. Focusing on projects is very important for SMEs because it has a big effect on the business. Organizations in different fields use different business models and frameworks. However, SMEs still don’t have a single, strong roadmap to follow. It brings together useful ideas of project management and AI techniques and gives SMEs built-in tools to help them set priorities and manage business projects.
By end-user, the banking, finance, and insurance segment is anticipated to grow with the highest CAGR over the forecast period. In an era where cyber crimes and frauds are the most common in the finance sector, AI-based project management solutions take a keen look at stakeholders and policies.
Regarding region, AI-based project management is anticipated to have the greatest share in North America. The demand for AI in the project management market is fueling in North America with the growing number of key players and quick adoption of advanced technologies.
The major companies operating in the global AI in project management market include IBM, Oracle, Hitachi, Adobe, Microsoft, TIS, Service Now, Alice Technologies, Bubblz, Clear Strategy, Code Complete, Wrike, and others.
In February 2023, Hitachi released the new generation TXpert Hub to digitalize transformers. The TXpert Hub makes monitoring possible by collecting, storing, and analyzing the data from the transformer's digital sensors.
In January 2023, TIS Inc. and Vector Consulting Group agreed to share capital and do business together.
In December 2022, IBM signed a deal to acquire Octo, a US-based IT modernization and digital transformation services company.
By Component
By Application
By Deployment Mode
By Organization Size
By End User
By Region
Frequently Asked Questions
AI-driven project management optimizes resource utilization, reduces waste, and enhances operational efficiency, thereby contributing to sustainability goals globally. It enables organizations to achieve more with fewer resources, aligning with the principles of environmental conservation.
Ethical considerations include bias in AI algorithms, data privacy issues, transparency in decision-making, and the impact on employment. Addressing these concerns is crucial for ensuring responsible and ethical AI adoption in project management practices globally.
AI enables real-time data analysis, predictive modeling, and scenario planning, empowering organizations to respond quickly to changes in the global business landscape. It enhances agility, adaptability, and resilience, ensuring competitiveness in dynamic markets.
AI enables continuous performance monitoring, identifies areas for improvement, and provides actionable insights for optimizing project performance globally. By analyzing vast datasets and identifying trends, AI helps organizations refine strategies and achieve better project outcomes.
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