• Flexibility: Agile approaches prioritize flexibility and the ability to adapt to changing requirements and circumstances easily. That’s advantageous in today's fast-paced business environment.
• Faster Time-to-Market: Agile approaches emphasize quick delivery of working products or services, which enables businesses to rapidly respond to market demands and gain a competitive edge.
• Customer-centric: Agile approaches focus on delivering value to customers, which helps businesses to better understand their needs and deliver products or services that meet those needs.
• Collaboration: Agile approaches encourage collaboration and communication between team members, which helps to create a more cohesive and productive team.
• Continuous improvement: Agile approaches prioritize continuous improvement, allowing teams to reflect on their performance and adjust their approach as needed to improve productivity and efficiency.

• Twitter,
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• LinkedIn.

• Implement and use the most popular agile framework―Scrum;
• Deliver products in short cycles with rapid adaptation to change, fast time-to-market, and continuous improvement; and
• Support innovation and drive competitive advantage.

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• 🌏 More countries

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• 🇦🇹 Austria
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• 🇫🇷 France
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• 🇬🇷 Greece
• 🇮🇳 India
• 🇮🇪 Ireland
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• 🇱🇺 Luxembourg
• 🇲🇽 Mexico
• 🇳🇱 Netherlands
• 🇳🇿 New Zealand
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Tags: #Agile • #AgileAdoption • #AgileCoach • #AgileProductManagement • #AgileMindset • #AgileProjectManagement • #AgileEvolution • #AgileQA • #AgileScrum • #AgileTeams • #AgileTesting • #AgileTradecraft • #AgileTransformation • #AgileTrends • #FutureOfAgile • #FutureOfWork • #ScrumMaster • #DigitalTransformation • #BusinessAgility • #AgileValues • #Agility • #AgileScaling • #AgileFuture • #AgileInnovation • #AgileKanban • #AgileLearning • #AgileLeadership • #AgileEngineering • #AgileDelivery • #AgileCollaboration

• Programming Languages and Algorithms: Proficiency in programming languages such as Python, Java, or R is essential. These languages enable team members to write efficient code, manipulate and analyze data, and implement machine learning algorithms. Understanding algorithms, from classic ones like linear regression to cutting-edge deep learning models, empowers AI professionals to leverage mathematical principles and statistical techniques to train and optimize AI systems.
• Data Analysis and Management: AI relies on data, making data analysis and management skills crucial. AI team members need to be adept at collecting, cleaning, and preprocessing data, ensuring its quality and relevance. They must possess the knowledge of statistical methods, data visualization techniques, and data engineering practices to extract insights from complex datasets and prepare them for AI model training.
• Machine Learning and Neural Networks: Technical skills in machine learning are at the heart of AI systems. Understanding machine learning algorithms, such as decision trees, support vector machines, or convolutional neural networks, enables AI team members to create models that can learn from data and make intelligent predictions or decisions. Expertise in neural networks and deep learning architectures equips professionals with the ability to develop complex models capable of handling tasks like image recognition, natural language processing, and reinforcement learning.
• AI Frameworks and Tools: Proficiency in AI frameworks and tools (such as TensorFlow, Keras, PyTorch, Caffe, Scikit-learn, and others) are essential for building AI systems efficiently. These frameworks provide pre-built modules, libraries, and APIs that simplify the implementation of AI algorithms and models. Technical skills in utilizing these tools effectively enable AI team members to accelerate the development process, streamline model training, and optimize system performance.
• Domain Knowledge and Application-Specific Skills: Technical skills also encompass domain knowledge and application-specific expertise. Understanding the nuances of the industry or problem domain in which AI is being applied allows professionals to tailor AI solutions to meet specific requirements. For example, healthcare-focused AI projects may require knowledge of medical terminologies and regulatory considerations, while AI solutions for financial services may demand expertise in risk assessment and fraud detection.

• Effective Communication and Technical Expertise: Communication bridges the gap between AI professionals and others who may not possess technical backgrounds. AI experts with strong communication skills can articulate complex technical concepts in plain English, ensuring that everyone involved understands the goals, challenges, and progress of the project. By effectively conveying ideas, AI professionals foster collaboration, gather valuable insights, and create a shared vision for AI initiatives.
• Collaboration and Problem-Solving: Collaboration is at the core of AI development, and soft skills such as teamwork, empathy, and active listening facilitate effective collaboration among diverse team members. AI teams with strong collaboration skills can effectively pool their technical expertise, brainstorm ideas, and solve complex problems together. By leveraging their collective intelligence and diverse perspectives, AI teams can overcome challenges, refine AI models, and optimize the performance of AI solutions.
• Critical Thinking and Technical Innovation: Critical thinking, coupled with technical expertise, leads to innovative AI solutions. AI professionals with strong critical thinking skills can evaluate different approaches, challenge assumptions, and identify potential shortcomings or biases in AI models. They can think creatively to address issues such as data biases or fairness concerns, ensuring that AI systems are developed responsibly and ethically.
• Leadership and Team Empowerment: Effective leadership in AI projects involves establishing and maintaining a collaborative and inclusive environment, empowering team members, and harnessing their full potential. AI leaders with exceptional interpersonal abilities can inspire and motivate their team, foster a culture of continuous learning, and provide guidance in navigating complex technical challenges. They encourage interdisciplinary collaboration, respect diverse perspectives, and drive the team towards achieving AI objectives.

• Training Programs and Workshops: Implement specialized training programs and workshops focused on enhancing soft skills. Offer courses in effective communication, leadership (including how to navigate the phases of team development), problem-solving, critical thinking, and collaboration. These programs can provide AI professionals with the necessary tools and techniques to effectively apply soft skills in their work.
• Interdisciplinary Collaboration and Knowledge Sharing: Encourage interdisciplinary collaboration by creating opportunities for AI team members to work alongside experts from diverse fields such as psychology, design, ethics, and business. This collaboration allows for cross-pollination of ideas, encourages different perspectives, and broadens the skill set of AI teams. Foster a culture of knowledge sharing, where professionals can learn from each other and leverage their collective experiences and expertise.
• Real-World Project Engagement: Provide AI team members with opportunities to work on (other) real-world projects, allowing them to apply their soft skills in practical scenarios. Engaging in projects that involve interaction with clients, end-users, and stakeholders helps AI team members develop effective communication, problem-solving, and teamwork skills.
• Continuous Learning and Professional Development: Encourage AI team members to engage in continuous learning and professional development activities. This can include attending conferences, participating in webinars, reading industry publications, and pursuing certifications in relevant areas. Promote a growth mindset among AI team members, emphasizing the importance of lifelong learning and staying current with the latest developments in both technical and soft skills domains.
• Mentorship and Coaching: Establish mentorship and coaching programs where experienced AI professionals guide and support individuals with less experience. Mentors can provide valuable insights, share their experiences, and offer guidance on developing skills. Regular feedback and coaching sessions help AI professionals identify areas for improvement and provide targeted development opportunities.

• Accenture (2023, March 30). Accenture Technology Vision 2023: Generative AI to Usher in a Bold New Future for Business, Merging Physical and Digital Worlds. Available at: https://newsroom.accenture.com/news/accenture-technology-vision-2023-generative-ai-to-usher-in-a-bold-new-future-for-business-merging-physical-and-digital-worlds.htm.
• Alsever, Jennifer (2020, January 20). Medicine by Machine: Is A.I. the Cure for the World’s Ailing Drug Industry? Fortune. Available at: https://fortune.com/longform/ai-artificial-intelligence-medicine-healthcare-pharmaceutical-industry.
• Berlin School of Business and Innovation (2022, September 22). How Do Technical Abilities Combined with Leadership Skills Fuel Career Growth? Available at: https://www.berlinsbi.com/blog/career-advice/how-do-technical-abilities-combined-with-leadership-skills-fuel-career-growth.
• Bhatti, Shawaiz, Demir, Mustafa, Cooke, Nancy J., & Johnson, Craig J. (2021). Assessing Communication and Trust in an AI Teammate in a Dynamic Task Environment. In: 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS): 1–6. DOI: 10.1109/ICHMS53169.2021.9582626.
• Brooks, David (2023, February 2). In the Age of A.I., Major in Being Human. The New York Times. Available at: https://www.nytimes.com/2023/02/02/opinion/ai-human-education.html.
• Crampton, Natasha (2021, January 19). The Building Blocks of Microsoft’s Responsible AI Program. Microsoft. Available at: https://blogs.microsoft.com/on-the-issues/2021/01/19/microsoft-responsible-ai-program.
• Dolev, Niva, & Itzkovich, Yariv (2020). In the AI Era, Soft Skills are the New Hard Skills. In: Artificial Intelligence and Its Impact on Business, pp. 55-77. Charlotte, NC: Information Age Publishing.
• Dzombak, Rachel, & Palat, Jay (2021, August 30). 5 Ways to Start Growing an AI-Ready Workforce. Pittsburgh, PA: Software Engineering Institute, Carnegie Mellon University.
• Elliott, Joshua (n.d.). Artificial Social Intelligence for Successful Teams (ASIST). Arlington, VA: Defense Advanced Research Projects Agency (DARPA).
• Fountaine, Tim, McCarthy, Brian, & Saleh, Tamim (2019). Building the AI-Powered Organization. Harvard Business Review, 97 (4): 62–73.
• Gartner (2020, December 15). How to Staff Your AI Team. Available at: https://www.gartner.com/smarterwithgartner/how-to-staff-your-ai-team.
• Gorman, Austin (2023, April 27). How to Strengthen Your Soft Skills for AI and the Future of Work. Fast Company. Available at: https://www.fastcompany.com/90887540/how-to-strengthen-your-soft-skills-for-ai-and-the-future-of-work.
• GovExec Events (2020, July 1). Human Machine Team: The Intersection of Diverse Skill Sets [Video]. Defense One. Available at: https://www.youtube.com/watch?v=93wbNLKpbxg&t=1s.
• Graffius, Scott M. (2023, May 1). Fueling the Development of Innovative and Life-Changing AI Solutions [Presentation]. Talk delivered to an audience of Technology professionals (including Data Scientists, Machine Learning Engineers, Data Engineers, AI Researchers, Project Managers, Business Analysts, UX Designers, Software Developers, Cloud Architects, Data Privacy and Security Specialists, and others involved or interested in AI) at a private event in Mountain View, California, United States. Digital Object Identifier (DOI): 10.13140/RG.2.2.27956.73601. DOI link: https://dx.doi.org/10.13140/RG.2.2.27956.73601.

• Graffius, Scott M. (2023, April 26). The Science of High-Performance Teams [Presentation]. Talk delivered at the DevOps Institute’s SKILup Day 2023 Conference. Digital Object Identifier (DOI): 10.13140/RG.2.2.15888.28169. DOI link: https://dx.doi.org/10.13140/RG.2.2.15888.28169.

• Graffius, Scott M. (2023, January 9). Use the Phases of Team Development (Based on Bruce W. Tuckman's Model of Forming, Storming, Norming, Performing, and Adjourning) to Help Teams Grow and Advance: 2023 Update. Available at: https://scottgraffius.com. Digital Object Identifier (DOI): 10.13140/RG.2.2.10720.35846. DOI link: https://dx.doi.org/10.13140/RG.2.2.10720.35846.

• Graffius, Scott M. (2022, May 13). Want Happier and More Productive DevOps Teams? [Presentation]. Talk delivered at DevOpsDays Geneva, Switzerland 2022 Conference. Digital Object Identifier (DOI): 10.13140/RG.2.2.22252.85127. DOI link: https://dx.doi.org/10.13140/RG.2.2.22252.85127.

• Graffius, Scott M. (2021, October 5). Navigate the Phases of Team Development with Speed and Agility for Happier and More Productive Teams [Presentation]. Talk delivered at the Institute of Electrical and Electronics Engineers IEEE Day 2021 Conference. Digital Object Identifier (DOI): 10.13140/RG.2.2.20055.19365. DOI link: https://dx.doi.org/10.13140/RG.2.2.20055.19365.

• Graffius, Scott M. (2021, February 20). But First, the Team! [Presentation]. Talk delivered at the Brno, Czech Republic DevConf.CZ 2021 Conference. Digital Object Identifier (DOI): 10.13140/RG.2.2.29016.72964. DOI link: https://dx.doi.org/10.13140/RG.2.2.29016.72964.
• IBM (2019, September 26). Assemble the Team to Support a Data-Driven Project. Available at: https://www.ibm.com/garage/method/practices/culture/assemble-team-for-data-driven-project.
• IBM (2019). Everyday Ethics for Artificial Intelligence. Available at: https://www.ibm.com/watson/assets/duo/pdf/everydayethics.pdf.
• Institute of Electrical and Electronics Engineers (IEEE) (2021, November 8). The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. Available at: https://standards.ieee.org/industry-connections/ec/autonomous-systems.html.
• Kenan Institute (2023, February 20). The Must-Have Skills in the Era of Artificial Intelligence: How AI’s Democratization Will Impact Workers. Available at: https://kenaninstitute.unc.edu/commentary/the-must-have-skills-in-the-era-of-artificial-intelligence-how-ais-democratization-will-impact-workers.
• Lindzon, Jared (2017, February 28). How AI is Changing the Way Companies are Organized. Fast Company. Available at: https://www.fastcompany.com/3068492/how-ai-is-changing-the-way-companies-are-organized.
• Marr, Bernard (2023, March 20). Beyond The Hype: What You Really Need to Know About AI In 2023. Forbes. Available at: https://www.forbes.com/sites/bernardmarr/2023/03/20/beyond-the-hype-what-you-really-need-to-know-about-ai-in-2023.
• Massachusetts Institute of Technology (MIT) Lincoln Laboratory (2023, January 17). Human-AI Performance Incubator. Available at: https://www.ll.mit.edu/r-d/projects/human-ai-performance-incubator.
• Massachusetts Institute of Technology (MIT) (2021, January). Cognitive Science as a New People Science for the Future of Work. Available at: https://workofthefuture.mit.edu/wp-content/uploads/2021/01/2021-Research-Brief-Polli-Kassir-Dolphin-Baker-Gabrieli.pdf.
• Massachusetts Institute of Technology (MIT) Sloan (2019, October 15). Winning With AI. MIT Sloan Management Review and Boston Consulting Group. Available at: https://sloanreview.mit.edu/projects/winning-with-ai.
• McNeese, Nathan J., Demir, Mustafa, Chiou, Erin K., & Cooke, Nancy J. (2021). Trust and Team Performance in Human–Autonomy Teaming. International Journal of Electronic Commerce, 25 (1): 51–72. DOI: 10.1080/10864415.2021.1846854.
• Mearian, Lucas (2023, February 24). Skills-Based Hiring Continues to Rise as Degree Requirements Fade. Computerworld. Available at: https://www.computerworld.com/article/3689170/skills-based-hiring-continues-to-rise-as-degree-requirements-fade.html.
• Microsoft (2019, June 15). Is the Latest Technology the Key to Your Team’s Success, or is There Something Else? Available at: https://devblogs.microsoft.com/premier-developer/is-the-latest-technology-the-key-to-your-teams-success-or-is-there-something-else.
• New South Wales Technical and Further Education Commission (TAFE NSW) (2019). Soft vs. Hard Skills: Why Successful Australian Businesses Need Both. Ultimo, New South Wales: TAFE NSW.
• O’Dea, Blathnaid (2023, February 17). These are the Top Skills AI and Analytics Professionals Need. Silicon Republic. Available at: https://www.siliconrepublic.com/advice/top-skills-ai-data-analytics-professionals-need.
• Organization for Economic Cooperation and Development (OECD) (n.d.). OECD Programme on AI in Work, Innovation, Productivity and Skills. Available at: https://oecd.ai/en/work-innovation-productivity-skills/key-themes/skills.
• Oswald, Andrew. J., Proto, Eugenio, & Sgroi, Daniel (2015). Happiness and Productivity. Journal of Labor Economics, 33 (4): 789-822.
• Project Management Institute (2020, March 10). Tomorrow's Teams Today: The Future of Teaming: Creative, Collaborative and Agile. Pulse of the Profession. Available at: https://www.pmi.org/learning/library/pulse-indepth-tomorrows-teams-today-11941.
• PwC (2017). Sizing the Prize: What’s the Real Value of AI for Your Business and How Can You Capitalise? PwC’s Global Artificial Intelligence Study: Exploiting the AI Revolution. Available at: https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html.
• Rayside, Derek (Ed.) (2023, March 29). Software Engineering Capstone Design Project Handbook (2023 Edition). Waterloo, Ontario, Canada: University of Waterloo.
• Romsey, Joseph (2020, November 30). 5 Tips to Help Workers Upskill and Adapt to Artificial Intelligence. Society for Human Resource Management (SHRM). Available at: https://www.shrm.org/resourcesandtools/hr-topics/technology/pages/how-hr-can-help-workers-upskill-and-adapt-to-artificial-intelligence-5-tips.aspx.
• Stanford University (2019, September). Gathering Strength, Gathering Storms. Stanford, CA: Stanford University.
• Tredinnick, Luke (2017). Artificial Intelligence and Professional Roles. Business Information Review, 34 (1): 37–41.
• Ungerleider, Neal (2023, January 1). AI and Jobs: The Human Angle. Available at: https://www.sap.com/denmark/insights/viewpoints/ai-jobs-human-angle.html.
• United Nations Educational, Scientific and Cultural Organization (UNESCO) (2021, July 2). AI Ethics: Another Step Closer to the Adoption of UNESCO’s Recommendation. Available at: https://en.unesco.org/news/ai-ethics-another-step-closer-adoption-unescos-recommendation-0.
• United States Artificial Intelligence Institute (USAII) (2022). Factsheet: Fast-Track Your Artificial Intelligence Career in 2023. Stamford, CT: USAII.
• United States Congress Committee on Science, Space, and Technology (2019, September 24). Artificial Intelligence and the Future of Work. Report for the One Hundred Sixteenth Congress. Available at: https://www.congress.gov/116/chrg/CHRG-116hhrg37740/CHRG-116hhrg37740.pdf.
• University of Leeds (2023, March 2). The Top 5 AI Skills You Need to Land a Job in Artificial Intelligence. Available at: https://pg-online.leeds.ac.uk/blogs/5-skills-needed-for-ai.
• World Manufacturing Foundation (2020). 2020 World Manufacturing Report: Manufacturing in the Age of Artificial Intelligence. Available at: https://worldmanufacturing.org/wp-content/uploads/WorldManufacturingForum2020_Report.pdf.

• Twitter,
• Facebook, and
• LinkedIn.

• Implement and use the most popular agile framework―Scrum;
• Deliver products in short cycles with rapid adaptation to change, fast time-to-market, and continuous improvement; and
• Support innovation and drive competitive advantage.

• 🇦🇺 Australia
• 🇦🇹 Austria
• 🇧🇪 Belgium

• 🇧🇷 Brazil
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• 🇩🇰 Denmark
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• 🇱🇺 Luxembourg
• 🇲🇽 Mexico
• 🇳🇱 Netherlands
• 🇳🇿 New Zealand
• 🇳🇴 Norway
• 🇪🇸 Spain
• 🇸🇪 Sweden
• 🇨🇭 Switzerland
• 🇦🇪 UAE
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• 🌏 More countries

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• 🇬🇷 Greece
• 🇮🇳 India
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• 🇱🇺 Luxembourg
• 🇲🇽 Mexico
• 🇳🇱 Netherlands
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Tags: #Accenture • #BSBI • #FastCompany • #MIT • #Gartner • #IBM • AI team • #AITeam • AI team skills • #AITeamSkills • Developing and Advancing Soft Skills in AI Teams • The Power of Synergy: Soft Skills and Technical Skills in AI Teams • The Role of Technical Skills in AI Teams • Understanding Soft Skills in AI Teams • United States Artificial Intelligence Institute • Stanford University • Software Engineering Institute • Microsoft • MIT • IEEE • IBM • DARPA • Graffius' work on AI projects • AI teams • AI • Artificial Intelligence • #AIForGood • #MachineIntelligence • #techinnovation • #AISkills • #AISoftSkills • #AIJobs • #ArtificialIntelligenceSkills • #ArtificialIntelligenceTeamSkills • #ArtificialIntelligenceSoftSkills • #AIResearch • #MI • #AIIsATeamSport • #BigData • #Collaboration • #Data • #Development • #DeepLearning • #AgileBlog • #Keras • #TensorFlow • #Caffe • #PyTorch • #ScikitLearn • #BusinessBlog • #TechnologyBlog • #ProjectManagementBlog • #Leadership • #Tech • #Teamwork • #AIStory • #Technology • #Blog • #TechnicalSkills • #TeamLeadership • #TeamDevelopment • #TeamCollaboration • #TeamBuilding • #SoftSkills • #Team • #ProjectManager • #ProjectManagement • #Management • #ML • #MachineLearning • #Innovation • #Future • #Entrepreneurship • #Engineering • #ChangeManagement • #ArtificialIntelligence • #AIteams • #AI • #Agile • #PwC • #Startups • #Science • #NeuralNetworks • #Programming • #AITradecraft • #autonomousSystems • #USAII • #FutureOfWork • #DataScience • #CognitiveComputing • #emergingtech • #IEEE • #Microsoft • #CoreSkills • #Interpersonalskills • #PeopleSkills • #transferableskills • #transversalskills • #PowerSkills • AI Skills • AI teams • AI Soft Skills • AI Hard Skills • AI team skills • AI technical skills • AI interpersonal skills

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• Myron Giannakis,
• Peter Den Haan,
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• Sara Marzella, and
• Alberto García García.

• Twitter,
• Facebook, and
• LinkedIn.

• Implement and use the most popular agile framework―Scrum;
• Deliver products in short cycles with rapid adaptation to change, fast time-to-market, and continuous improvement; and
• Support innovation and drive competitive advantage.

• 🇦🇺 Australia
• 🇦🇹 Austria
• 🇧🇪 Belgium

• 🇧🇷 Brazil
• 🇨🇦 Canada
• 🇨🇿 Czech Republic
• 🇩🇰 Denmark
• 🇫🇮 Finland
• 🇫🇷 France
• 🇩🇪 Germany
• 🇬🇷 Greece
• 🇭🇺 Hungary
• 🇮🇳 India
• 🇮🇪 Ireland
• 🇮🇱 Israel
• 🇮🇹 Italy
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• 🇱🇺 Luxembourg
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• 🇳🇿 New Zealand
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