This framework is developed by a team of former McKinsey and Big 4 consultants. The presentation follows the headline-body-bumper slide format used by global consulting firms.
Artificial Intelligence PPT: Learn AI strategy priorities, business models, and implementation examples. Download this actionable AI Strategy PowerPoint (PPTX) now. AI Strategy: Top Priorities is a 26-slide PPT PowerPoint presentation slide deck (PPTX) available for immediate download upon purchase.
Revamping traditional systems, implementing AI, and scaling, in reality, is not as simple as it seems. PwC's 2020 Research validates that scaling and industrializing AI is not straightforward at all. Only 4% of the survey respondents asserted that they plan on implementing organization-wide AI in 2020. Whereas, a year earlier, the same survey revealed 20% of the executives planning to do that.
This shows a significant decrease in the number of senior leaders thinking of executing AI. The reason for this drop is attributed mainly to the lack of preparedness required for enterprise-wide AI implementation.
This presentation talks about the 5 key priorities of a robust AI Strategy that businesses should follow to position themselves as AI leaders:
1. Boring AI
2. AI-ready Workforce
3. Responsible and Ethical AI
4. AI Operationalization
5. Business Model Innovation (BMI)
The slide deck also includes some slide templates for you to use in your own business presentations.
AI technology is reshaping enterprise structures, decision-making processes, and research and development. This presentation underscores how AI can fundamentally alter organizational operations, driving productivity and creating new job roles. It emphasizes that AI should be integrated with other technologies and not deployed in isolation to avoid potential pitfalls.
Executives must recognize the importance of an AI-ready workforce, upskilling employees to handle AI and machine learning technologies. This PPT provides insights into the critical steps for operationalizing AI across multiple departments, ensuring data integration, and addressing AI-related challenges. It also includes templates to help you craft your own AI strategy presentations.
Boring AI refers to the automation of mundane administrative tasks, such as tax and finance functions. A PwC study reveals that 44% of business leaders believe AI enhances operational efficiency, while 42% see increased productivity as a key benefit. AI's ability to automate repetitive tasks can lead to significant time savings by minimizing human effort in data handling. To maximize AI's business value, leadership should develop strategies to identify impactful areas, build necessary capabilities, and integrate AI solutions with existing systems. Implementing oversight mechanisms and establishing key performance indicators (KPIs) are essential for measuring productivity and aligning AI initiatives with organizational goals.
This PPT slide outlines top priorities for an AI strategy, emphasizing the need to overhaul legacy systems for effective AI implementation. Key priorities include:
1. AI Strategy - Establishing a clear and actionable strategy for AI.
2. AI-ready Workforce - Equipping the workforce with necessary AI skills.
3. Responsible and Ethical AI - Committing to ethical AI practices for trust and compliance.
4. Operationalization - Integrating AI into existing operations seamlessly.
5. Business Model Innovation - Rethinking business models to leverage AI capabilities.
A PwC survey indicates that complexities in planning and managing AI initiatives contribute to organizational hesitation. Most perceive AI as presenting more opportunities than risks, highlighting the importance of a structured AI strategy.
This PPT slide focuses on operationalizing Artificial Intelligence (AI) within organizations, emphasizing the need for integration across business units and technological frameworks. AI must be embedded throughout operations, including marketing and finance, and integrated into the IT infrastructure to maximize its value. Building machine learning into production processes is essential for practical application. Specialized methodologies and tools are necessary for AI development, differing from traditional software delivery. Effective data management, including labeling and categorization, is crucial, requiring robust governance and skilled teams. Active learning enhances data categorization, with data scientists refining algorithms. AI should align with broader transformation initiatives like automation and analytics for optimal effectiveness.
Organizations must develop an AI-ready workforce, moving beyond traditional training to dynamic skill development. Research shows that rewarding employees for applying training in real-world scenarios enhances problem-solving capabilities and productivity, indicating a shift from passive learning to active application. Cross-skilling is a key strategy, fostering collaboration among specialists from various domains to effectively address AI-related challenges. This approach enhances technical skills and integrates essential business acumen. Tailored training is crucial for roles like engineers and data scientists, who need specialized guidance in AI model development and data governance. A comprehensive strategy combining broad skill development, specialized training, and real-world application is essential for improving efficiency and innovation in AI initiatives.
This PPT slide presents findings from a 2020 PwC Research survey of 1,062 business leaders on the challenges of implementing Artificial Intelligence (AI) at an organizational level. In 2019, 20% of respondents planned for organization-wide AI implementation,, but this dropped to 4% in 2020, indicating increased awareness of the complexities in scaling AI technologies. The survey reveals that 42% of executives are still investigating AI uses, 23% are conducting pilots, and 18% have implemented AI in multiple areas. Only 13% plan for multi-area deployment, and just 4% aim for enterprise-wide implementation. Organizations must focus on foundational elements and phased approaches, prioritizing pilot programs before broader AI strategies.
Source: Best Practices in Artificial Intelligence, Business Model Innovation, Business Ethics PowerPoint Slides: Artificial Intelligence (AI) Strategy: Top Priorities PowerPoint (PPTX) Presentation Slide Deck, LearnPPT Consulting
This framework is developed by a team of former McKinsey and Big 4 consultants. The presentation follows the headline-body-bumper slide format used by global consulting firms.
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