Historically, Artificial Intelligence development has been the purview of universities. Inspired by the human genome project, this field of computer science seeked to map brains of humans, cats, and birds. The European Union has been investing a billion EUR to build an exact model of a human brain. America’s BRAIN initiative with 100 mn USD funding in 2014 alone has had similar goals.
At the same time, AI has rose to a prominence of a big tech trend of Silicon Valley. In 2013, Facebook opened an AI lab and recruited Yann LeCun, a leading AI mind, to be its director. In 2014, Google acquired for 400 million USD DeepMind, a London based firm, which Deep Learning outplayed several Go grandmasters and demonstrated remarkable self-teaching and adapting capabilities.
AI changed how Internet Champions operate and influence businesses across all sectors, including software development, healthcare and transportation. Five businesses under Fortune Top 10 have already declared to be “AI-First” in their strategies, while addressing three main competitive drivers to outsmart traditional businesses: data, infrastructure, and talent.
Artificial Intelligence implies a family of technologies and scientific fields that focus on automation, acceleration and extreme scalability of human perception (e.g. the capability to see, or to understand and speak a human language), decision-making and reasoning. Within AI Machine Learning (ML) is being one of the largest and fastest growing areas. ML algorithms learn from examples and experience rather than relying on predefined rules. Within ML there are different approaches or tribes, such as Deep Learning (DL), which focuses on deep neural network structures.
When AI emerged in the 1950s, the social sciences started to talk about it, using terms like “Artificial Narrow Intelligence”, “Artificial General Intelligence” and “Artificial Super Intelligence”.Top of Form We live in the era of Narrow AI, utilizing ML to automate business processes, transform customer experiences, and differentiate products offerings even without being capable to multitask.
AI is benefiting from affordable cloud computing infrastructure, availability of large datasets, and leaps in algorithm optimization. “The AI Imperative” assumes in the next 10 years we will see advanced neuromorphic chipsets, which will further enable Deep Learning, make it “explainable”, and further enabling quicker path to a “multi-tasking” AI. Besides, companies will see further progress in quantum software and hardware, and maybe even the emergence of a first universal quantum computer.
While traditional enterprise AI adoption is still in the early stages, the scale of the opportunity in AI demands more C-level attention and sponsorship. It is crucial then to have a concrete understanding of AI, its ecosystem, and how industry leaders are taking steps to drive unfair advantage from it.
Making the business fit for AI
If a company wants to make its business fit for AI, it has to fulfill several criteria.
It has to be skilled in data and understand, how data is collected, cleaned and prepared for AI processing.
It has to develop an IT infrastructure, powerful hardware and cloud allowing for AI training and product implementation.
It has to understand how to use open data sets and in the best case contribute to the openness in AI development and research.
Finally, it has to ensure there are governance practices around data and diversity on implementation teams to ensure safe and ethical use of technology.
Those working on these technologies are enthusiastic about their progress, including prospects to capitalize on this for their companies via M&A and organic growth opportunities.
At the same time there is a lot of confusion and lack of transparency over what AI implies and brings, how policymakers will react, and what is a proper operational strategy to address these new technologies to grow revenues and profitability.
Technology luminaries feel uncomfortable when asked to think end-to-end about the social, economic and environmental implications of what AI might bring. The disruptive impact of AI on jobs and employment, law enforcement, finance, healthcare, transportation, cyber security, consumer protection and privacy is enormous.
However good progress in North America and Europe to build safe and beneficial AI will be jeopardized by what has already started to happen in China. Chinese leaders addressed AI as their top strategic priority, promising to grow their domestic AI industry to 150 billion USD by 2030, while copying initiatives outlined in the AI plan as developed by the Obama’s White House.
“The AI Imperative” equips companies and their boards with the necessary tools to understand, address, tackle and undertake the changes in business strategy and governance necessary not only to survive the rapidly evolving competitive landscape but also to thrive and win.
The book aims at supporting a broader ecosystem of robotics and AI in a manner that is ultimately more balanced and progressive for humanity as a whole, and pushes the discussion of corporate sustainability to a new and uncharted level.
Buy the book here