Milan Dordevic MBA, PMP is a certified project management expert, author, speaker, business and technology mentor for high-tech.
Artificial intelligence (AI) is reimagining the business world, boosting innovation and productivity, and helping organizations think bigger. Organizations can use AI to improve their products, processes and decision-making. Using the technology available today, organizations should be able to achieve organizational agility powered by AI.
Organizational leaders need to continuously drive change and evaluate which areas, and at what complexity, AI should be utilized to support company goals and further growth.
The impact of artificial intelligence is being felt across all industries. There are multiple examples of implementing AI in the supply chain, transportation, education, operations, marketing, and pretty much every industry that’s moving toward digitalization and switching from manual activities to technology-assisted ones. With the help of AI, companies are better equipped to fight disasters using AI decision-making algorithms, detect anomalies and predict future behavior. AI enhances automation and reduces the human-intensive labor and tediousness involved in forecasting and prediction analysis.
The pace of change has increased as a result of the rise of artificial intelligence. In addition, organizations are under greater pressure to respond rapidly to shifting conditions. Because of this shift in perspective, organizational transformation and growth are no longer viewed as one-off projects but rather as ongoing initiatives to which all members may and should contribute.
What is AI and how does it help with decision-making?
Techopedia defines AI well: “Artificial intelligence, also known as machine intelligence, is a branch of computer science that focuses on building and managing technology that can learn to autonomously make decisions and carry out actions on behalf of a human being.” Additionally, it’s important to remember that, “AI is not a single technology. It is an umbrella term that includes any type of software or hardware component that supports machine learning, computer vision, natural language understanding (NLU) and natural language processing (NLP).”
Some experts say the evolution or maturity of artificial intelligence can be divided into three stages: The first is assisted intelligence, where humans get insights from data and take action based on it. It is pure data-driven decision-making. Technologies like cloud computing, and using various tools for data processing, help us with data segmentation, validation and processing. By leveraging AI-powered datasets, businesses and organizations may improve the speed, accuracy, effectiveness and consistency of their decision-making processes. In contrast to human analysis, AI is capable of conducting error-free analyses of massive datasets.
The second stage is augmented intelligence, which takes the data processing a bit further. On top of existing information management systems, augmented intelligence employs machine learning (ML) capabilities to continuously enhance outcomes. It is a constant process of training the system, or learning over time, based on actions taken.
In the coming years AI will probably reach the third stage, the point of full automation. All processes and activities will be completely digitized and automated through workflows, and machines, bots and systems will act directly upon intelligence derived from them.
AI And Project Leadership
Research recently shared by Deloitte named the top five benefits of implementing AI in an organization: enhancing current product, optimizing internal operations, optimizing external operations, liberating workers to be more creative and helping leaders make better decisions.
Enhancing products with AI is different for each organization, based on their product core strength, industry and customer involvement, but using AI to improve processes can be applied to almost every organization.
Internal operations, such as scheduling, reminders, and follow-ups, can be handled by AI systems in project organizations with little to no human intervention. That’s just one of the many smart ways these technologies can help individuals save time: by making sure nothing gets overlooked in the midst of all their activities.
AI-based tools are helping managers and leaders prioritize and make the right decisions in each phase from planning to implementation. It helps process project data and discover patterns that could impact final project delivery.
Gartner predicts that AI will eliminate 80% of today’s manual project management tasks by 2030. Functions from planning to data collection and from tracking to reporting will be powered by AI, which can help predict outcomes using different data points like project size, contract type, and project management competence. Project sequencing based on requirements will also improve with automation. Using AI to automate and optimize project data sets will allow organizations to maximize project investment value, and recognize savings for product development and organizational growth.
Additionally, every project is prone to risks. AI can help predict defects or redundancies early in projects and assist in overall risk analysis and mitigation. It also helps managers accurately compute the number of people and resources required to complete a project—and to keep the project on track. With machine learning and AI, historical data such as planned start and end dates can be used to predict future projects’ realistic timelines.
AI might observe humans and make predictions based on their patterns. AI systems may observe projects and team member behavior, spotting tendencies and nuances that could be otherwise missed.
PMO as the center of project excellence is the right place to start with AI adoption in an organization.
To begin, executives must identify the essential areas where the PMO can use AI to reduce discrepancies in project and organizational success. Once the areas have been identified, AI has to be systematically implemented, monitored and adapted as needed. The more data is used, the more accurate it will be. This is a mindset shift from project management to project leadership. It is data-driven leadership that allows project leaders to assess prior results, including early project failure signals, and offer actionable recommendations.
The focus of PMOs and project managers will simply shift from tactical to strategic, leaving tactical and repetitive tasks to AI and bots while empowering project and organizational leaders to make strategic decisions. Powered with AI, the PMO will be able to make slight adjustments that will cumulatively yield substantial improvements to the business’s outcomes.
As more companies understand and invest in the power of AI, the speed of innovation will increase. It’s critical for companies to embrace the technology—or risk falling behind competition and losing a step in the marketplace.
Originally created at Forbes.com by Milan Dordevic
