Driving Innovation through AI and Data science.
Most industrialists today wonder how artificial intelligence (AI) is likely to upset their economic model. It must be said that the latest advances in this area: Chatbots, translation automated in real time, Robotic Process Automation and Machine Learning, just to name a few, are showing promise. They open the field of possibilities in matters of applications and new services.
These are some of the advances that the telecommunications industry should benefit from. All over the world, large operators invest a lot of money and mobilize their researchers to benefit from advances in AI.
This course will help you understand the challenges of artificial intelligence in telecoms, show you some of the key concepts of artificial intelligence and show you how to better identify the different possible applications of AI in telecoms.
You will also discuss advanced methods of statistical learning to solve artificial intelligence issues, how to use neural networks and associated architectures, design and analyze experiences to evaluate systems HRI (Male Interaction – Robot).
You should be able to understand how AI can help improve surveillance of production machines, preventing the failure of equipment by using concepts such as predictive maintenance and automatic resolution incidents or “self-healing”.
A basic understanding of Telecoms Technology and Business is recommended but not essential. A basic Knowledge of Statistics and an entrepreneurial and open mindset would be asset.
WHO SHOULD ATTEND?
- Senior Managers Leading AI efforts and tech teams
- Developers wanting to Know more about AI
- Information Architects who want to gain knowledge in AI
- Experienced professionals who would like more insight into using AI in their departments
BENEFITS FOR DELEGATES
- Identify the various types of AI.
- Explore the various usages of AI in Telecoms.
- Understand the customer experience, the operations and maintenance of networks and impacts that AI can make on this.
- Discuss the key challenges for managing AI implementations at scale.
- Identify the basic concepts of the AI data model.
- Understand important aspects which may affect the successful implementation of an AI strategy.
BENEFITS FOR THE ORGANISATION
- Enhance business sustainability by being prepared for AI technological advances
- Assess the potential for internal operational improvements using artificial intelligence as a catalyst.
- Consider cutting-edge AI opportunities in areas such as edge computing and network slicing that could favorably impact your organization
- Identify the key areas where AI is being used within of the telecoms industry.
- Make informed business decisions and build a business case related to the adoption of AI technologies in the context of Telecoms Operators
- Develop viable business strategies to maximize AI opportunities
WHAT MAKES THIS COURSE DIFFERENT?
- Delegates will have an opportunity to explore the topic by industry expert driven content.
- Real world case studies and scenarios are used to ensure delegates can practically apply their knowledge
- Cutting edge information delivered by future thinkers and industry influencers
- Highly interactive with facilitated strategy session, business model canvases and team collaboration to build a strategic plan for implementation in your business.
- The only course you’ll need to immediately develop viable business strategies to maximize AI opportunities! You leave informed and with a complete strategy to harness the advantage of data-centric AI enabled operations
NOTE: This course is not delivered with the FoldOut methodology.
What is AI? Definitions and background
- Introducing AI, definitions and market forecasts: Understanding the narrow and wider definitions of AI. Where AI fits into the global telecoms and digital landscape?
- Introducing AI, definitions and market forecasts: Understanding the narrow and wider definitions of AI.
- Who is who in AI. Understanding the startup ecosystem and market opportunity
Why AI in telecoms? The big picture
- Where AI fits into the global telecoms and digital landscape?
- Enabling platforms for artificial Intelligence.
- Current adoption of AI in Telecoms
- Current adoption in Telecoms client sectors
Emerging technologies in Telco
- How AI works: Customer service, operations and data management
- Case studies from the Telecoms sector
- Role of AI: Constraints (Data) and enablers (5G): Pitfalls to avoid in the Telecoms industry
Managing AI at scale
- AI IT and Operations Transformation. Driving cultural change: re-orientating the whole organization towards data-centric Innovation.
- Data ethics and diversity
- Use cases requiring high network performance levels
Developing an AI strategy
- Assess the impact of AI on the future of work and Society
- The future of AI in Business
- Develop a roadmap for your organization and build a strategic advantage through the use of AI
AI transformation enabling strategy
- How to prepare to fully embrace AI’s potential: Business and Technical diligence
- Framework for critical aspects of organizational strategic planning in Telco’s
- Practical use of AI for strategic innovation and competitive advantage
- Business models in an AI enabled world
- Critical foundations required to build successful AI programmes within the Telecoms industry: AI, strategy and organizational culture.
Innovation methodologies, building a culture of innovation
- Innovation principles
- The role of AI in innovation
- Agile leadership in Telecoms: What does it mean, what does it look like
- Project methodologies that are required for AI to succeed.
PRACTICAL INTERACTIVE STREAM (running throughout the 3 days)
- Problem definition and validation – selecting an opportunity to work on
- Exploring possible solutions
- Business model
- Competitor analysis
- Market analysis
- Data availability and regulatory issues
- Road map
- Funding requirements
- Case study on what value AI is bringing to telecommunications
- Impact that AI is having across industries and regions, and what can the telecommunications industry learn
- How to build an Agile Telco business as a pre-requisite for AI effectiveness
Case Study Presentations. Refine Lean Data Model Canvas for post course implementation.