Leading Businesss Transformation with Artificial Intelligence (AI)
Time commitment: 7 hours per week for 5 weeks.
How is this course taught? Online
The Leading Business Transformation with Artificial Intelligence (AI) programme provides participants with an overview of the range of AI technologies on the market, including machine learning (ML) and deep learning (DL), their application and associated challenges.
Participants will learn how to identify opportunities for creating business value through AI initiatives, and how to create an effective AI implementation roadmap while implementing organisational change management. It also shows delegates how to take ethical and human resources-related issues into account.
The course will provide case examples for effective AI implementation from different industries and sectors. It will equip participants with the tools to develop pilots and innovation agendas for their workplace as well as examine the impact of AI driven innovation on workforce productivity and satisfaction, including talent management and performance management.
Leading Business Transformation with Artificial Intelligence (AI) will also benefit organisation leaders in overcoming potential barriers to the adoption of AI initiatives in change management programmes.
There are no formal entry requirements for this course. However, a professional or general interest in AI and the opportunities and implications for the technology’s deployment within organisations is useful.
This programme has been designed for those in leadership roles working in various industries and sectors, to enable these individuals to implement and lead AI programmes for digital and business transformation within their own organisation.
Leading Business Transformation with Artificial Intelligence (AI) addresses key themes in two teaching sessions per week during the five-week programme:
- Week one, session one provides a general overview of enterprise AI, including AI in different industries and AI economics.
- Week one, session two provides an enterprise AI market overview, exploring examples of successful AI initiatives and technologies for enterprise transformation, while examining potential impacts of enterprise AI initiatives and identifying which ones are successful and why.
- Week two, session one is focused on developing an enterprise AI strategy, which shows participants how to identify business problems and explores ML and AI capacities to augment and automate. Participants will also find out how to develop a roadmap and data strategy.
- Week two, session two covers pilots and success criteria, such as (rapid) prototyping, devising a value proposition and defining outcomes and metrics.
- Week three, session one addresses change management and adoption, including identifying
- barriers to adoption and how to overcome these, and communicating and monitoring AI implementation.
- Week three, session two is focused on the AI-augmented workforce, including understanding and measuring productivity, understanding and measuring satisfaction and wellbeing, and managing impacts of AI implementation on satisfaction and wellbeing.
- Week four, session one covers ethical AI considerations. Topics span human augmentation, bias evaluation as well as trust and security risks.
- Week four, session two is concerned with IEEE and international standards, looking at developments, threats and opportunities and evaluating compliance of AI initiatives.
- Week five, session one provides delegates with the opportunity to bring together everything they have learned. It covers driving enterprise AI forward within organisations and designing AI initiatives for workforce augmentation.
- Week five, session two provides opportunity for presentations and feedback.
By the end of the course participants will be able to identify opportunities for creating business value through AI initiatives.
They will be able to create an effective AI implementation roadmap while taking organisational change management, as well as ethical and human resources related concerns into account.
This course is taught by several leading AI experts:
- Ivana Bartoletti, technical director at Deloitte. Ivana is a public speaker, author and media commentator. She consults to businesses on privacy-by-design programmes and is the author of ‘An Artificial Revolution’ and co-editor of the Fintech Circle’s AI Book on how AI is reshaping financial services.
- Lubna Dajani, advisory board member, evaluator and coach to Horizon 2020 NGI Trust. Lubna, a C-level executive, applies emerging information and communication technologies, systems thinking, and experiential design to drive digital innovation and organisational transformation. Lubna is also a credited contributor to IEEE standards bodies on ethical AI and autonomous and intelligent systems.
- Diane Mulcahy, advisor, institutional investor and the author of ‘Gig Economy and the Future of Work’. Her work on VC and private equity has been featured in the Wall Street Journal, the Economist, Fortune, Forbes, and The New Yorker. Mulcahy also created the first MBA course in the US on the gig economy.
- Dr Vijak Haddadi (PhD, MBA, MA), previously headed Digital Innovation at LSBU Business School, and is now co-founder and CEO of Syndikat, a digital transformation agency. Vijak is a digital innovation strategist who has worked in executive and consultancy roles with accelerators and innovation agencies in Europe and North America, advising and coaching start-ups.
- Dr Mohammad Ghasemi Hamed is an AI scientist with deep interest in business innovation. Mohammad is a co-founder of Metarooh Technologies, an Enterprise AI start-up which provides holistic intelligence for enterprise value chains. He has designed and implemented specialised AI solutions for governmental and private organisations.
- Raj Muppala is a business executive and entrepreneur helping businesses with innovation technology solutions in AI working with Fortune 100 companies. Raj is founder and CEO of HaiX, an AI company that has developed applications such as Alivecore, which provides real-time brand reputation, risk and sentiments from millions of data points.
The course will be taught entirely online via LSBU’s learning platform.
The course will total approximately 35 hours teaching time, running two 3.5 hour sessions per week, for 5 weeks.
There is no formal assessment for this course.
There is no formal accreditation for this course. By the end particpants will be able to identify opportunities for creating business value through AI initiatives, design an AI implementation roadmap while taking organisational change management, as well as ethical and human resources-related concerns into account.
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