“The Internet has already disrupted about 20 percent of global economy, and AI will transform the rest. That means that 80 percent of the economy is getting transformed by Artificial Intelligence as we speak.”
We had the opportunity to interview Anastassia Lauterbach, who has served as Board Director of Dun & Bradstreet since 2013 and is the Chairwoman of their Technology & Innovation Committee and also serves as Board Director at Wirecard AG. She works on several boards, runs a boutique advisory company around Artificial Intelligence, Internet of Things and Cybersecurity and she invests in tech ventures.
Anastassia is also the leading author of the business book “Artificial Intelligence Imperative. A Roadmap for Businesses , published in April 2018 by Praeger. We will revisit the book further in this blog post.
Anastassia believes that Artifical Intelligence, AI, will transform most of our industries and societies, it will have high interdisciplinary impact, and that we as board directors need to stay knowledgeable and engaged in this transformation.
Listen to the interview with Anastassia Lauterbach in this episode from our podcast Exploring Leaders and learn about her journey and what she believes in.
About Anastassia Lauterbach
Anastassia Lauterbach started out with more than 20 years in insurance at Munich Reinsurance Company, advisory at McKinsey, at Daimler Chrysler Financial Services and moved into the telecom industry serving at Deutsche Telekom and T-Mobile. During 2011-13 she was the SVP Europe at Qualcomm, a world leader in wireless technologies.
She now serves at boards as Dun & Bradstreet and Wirecard AG, as Chairwoman of Censhare AG, a European private content aggregation provider and she is member of the Advisory Council Next Generation Directors for Nasdaq. She is also the founder of 1AU-Ventures and advices AI and cybersecurity companies and Investment Funds.
Anastassia also advises boards and leadership teams.
“Artificial intelligence is something incredibly practical” she says. “It’s getting embedded everywhere. It is an exciting time as all companies from insurance, energy, retailers to health care providers are now technology businesses.” –Anastassia Lauterbach
She believes it is all about how data can improve what the organizations are doing, what infrastructure should be put in place, to process the data, to improve user experience, technology is embedded in the texture of any business and it has become very strategic and very prominent.
Lauterbach also points out some of the challenges
“AI has a capability to scale everything we are about as humans, so if you have a team of only white male developers or only Chinese male developers, then you will get a data set or some algorithms that are wired according to preferences, habits and thinking processes of those groups.”
It is the leaders’ and boards’ responsibility to ensure diversity and ethical behaviour she advices.
Learn from Artificial Intelligence Imperative: A Practical Roadmap for Business
Anastassia has been the leading author of the business book Artificial Intelligence Imperative: A Practical Roadmap for Business. The book is written for leaders and for people with less background in technology, asking questions like
- What is the difference between AI concepts as machine and deep learning?
- What are IBM and other providers doing, can tools like Watson help us?
- Why do they need so much data?
- Should we give them our data?
We outline the main content and the value of the book below.
The first section of the book starts with describing the history and future of Artificial Intelligence and continues with enablers and preconditions to achieve AI.
Part One (Chapter 1-5) – The Past, Present, and Future of AI
This section covers a history of AI, AI social-science concepts, cognitive and machine learning approaches, AI technologies from computer vision to drones and linkages to blockchain, Internet of Things, Cybersecurity and quantum computing.
It shares insights as AI is an interdisciplinary topic, taking inspiration from biology, neuroscience, physics, mathematics, computer science, and the engineering of artificial neural systems. And that AI as academic field started already in 1955, with a breakthrough in 1997 when IBM’s Deep Blue defeated the reigning World Chess champion, Garry Kasparov. In 2004 the first contest in self-driving vehicles was held, in 2012 engineers without medical expertise, created an algorithm to more accurately diagnose breast cancer with the input of thousands of screening images.
Many of the AI concepts are explained with examples. Prominent AI fields are revisited as computer vision (for example needed by autonomous driving), language processing (including bots and chatbots that revolutionizes customer service), robotics (including drones that disrupts oversight and logistics), and emotion measurement technology (that facilitates oversight and error handling).
Part two (Chapter 6-9)– Enablers and Preconditions to Achieve AI
This section covers Data, Algorithms, Hardware, and Openness. Here we will learn that Data is the most important AI ingredient.
“We expect that new businesses around data preparation and collection will emerge dedicated to transforming data from a liability into a strategic asset.”
The book outlines that several factors enabling AI progress as growth in data, an evolution of algorithms, advances in semiconductors, cloud technologies, smart networks, and openness in libraries, frameworks, APIs and AI platforms.
The next section is focusing on the take-up and usage of AI, who are dominating and how different industries applying AI.
Part Three (chapter 10-15) – The Race for AI Dominance
This section includes AI from Academia and Private, Geopolitics, current competing providers and their battle, Domain focused Machine Learning, the focus of traditional versus new companies and introducing AI into traditional Business.
We learn that it is a fast-evolving discipline and that there is fierce competition among the dominant AI companies such as Alphabet/ Google, Apple, Facebook, Microsoft, and Amazon.
The authors believe that
“the right combination of Machine Learning and Blockchain technologies could make traditional companies thrive. Firms should neither fear nor be charmed by new technology. The key is to hire the right people who can translate technologies into a realistic strategy and provide a transformational roadmap.”
They continue to share myths and what areas to address to introduce AI.
Part Four (chapter 16-21) – AI in Different Sectors
This section provides an overview of some of the industry- and sector-specific AI technologies from the automotive to military sectors, from predicting a company’s earnings to identifying a tumor in a CT scan.
Here we can read about the different industries and their applications but also about specific examples.
“Siemens, for example, is using a neural model that alters the distribution of fuel in a turbine’s burners to increase efficiency. Siemens is also deploying cognitive technology by Watson to deliver predictive, prescriptive, and cognitive analytics within the industrial cloud platform MindSphere.”
The last section outlines the challenges around ethics and governance of AI highly relevant for leaders and board members
Part Five (Chapter 22-24) – The Socio-Politics of AI
This section shares insights about data control, AI, and societies, the future of employment and ethical design and social governance.
The authors share some of the ongoing development in society today and point out that technology can be used for both good and bad and that it is up to leaders to take charge. They also outline the importance and change in lifelong learning.
“We believe that the loss of jobs that will ensue is not because there is too much employment but because there is too little innovation. Responsible leaders at every level— both corporate and governmental as well as at the board, executive, and managerial levels— must start to address shifts in employment at the early stage of technology deployment and not think of technology as a way to cut costs and eliminate jobs, but rather as a way to innovate and create relevant new jobs.”
Part Six (chapter 25-26) – The Governance of AI
These last chapters we note are of special high value to leaders and boards and they cover “Traditional Boards Readiness to address AI – transforming fear into value” and “Discussing AI in the Boardroom”. Here the authors point out that visionary boards adapt their agendas and spend more time on technology, IT transformation, data security, and digital customer interfaces.
“Business sustainability is no longer about complementing the corporate roadmap with the skills of a few acquired startups, or assessing environmental and labor policies at suppliers, or complying with European data-protection regulations. It is about the profound impact emerging technologies are having on profits, succession planning, workforce training, and the possible automation of so many processes.”
Some challenges that need addressing are that the current setup of committees are more shaped by regulations and focused on compliance and that regulatory frameworks have always trailed technological change leaving grey areas around labor relationships, data protection etc.
The authors have identified the key elements that are needed to revisit for an AI evaluation, Strategy and Governance formulation;
- Competitive Landscape: Traditional and Disruptive
- Current Products and Services Interface
- Big Data and AI Interface
- Labor Force Impact
- Corporate Culture Impact
- Ethical Analysis
- M& A Opportunities
- R& D Opportunities
- Investor Impact/ Needs
- Customer Impact/ Needs
- Other Stakeholder Impacts
- Enterprise Risk Management Integration
- Strategic Risk and Opportunity Evaluation
“Data is one of the most important assets of any business. AI only works well when a company can clearly (1) state a problem that it wants to solve with data; (2) address a part of its operations that it wants to automate for better efficiency and quality; or (3) want to achieve insights it currently does not have or struggles to get in a cost-efficient way.”
The authors outline a phased approach explaining the key elements of an effective AI governance approach, with critical questions that any board should undertake for each phase.
The book includes useful questions to explore for each phase as for example
In Phase I: Whole Board Strategic Discussion on a Data Value Strategy –
- What unique data do we currently hold on our customers, suppliers, and partners? What is their strategic value? Which company among our current suppliers and competitors would like to have our data and why?
- Do we use and should we use real-time (streaming) data to achieve competitive advantage in strategic positioning, operations, and regulatory reporting?
- What data assets are most vulnerable from a cybersecurity point of view? What systems incorporate these data? Where are the cyber-vulnerable “crown jewels”?
In Phase VII: Types of AI Technology Needed?
- What AI capabilities should our company own? Where should we partner, and what should we outsource?
- What are the possibilities and opportunities for co-competition scenarios with our partners and suppliers?
The book holds many more questions and further guidance to boards to ensure they start to take ownership of the emerging AI governance.
We highly recommend this book to leaders and boards that want to stay relevant in the future and to start to get a grip on the challenges and opportunities for their own organizations to use AI.
You find the book at several bookstores and at Amazon here.
Inspiration from Anastassia
In our interview, we asked Anastassia Lauterbach about what companies and leaders we should keep our eyes on. She shared that the most valuable companies are now all digital companies, the five in top are Alphabet, Google, Apple, Amazon, and Microsoft and we should understand how those companies are working.
She also recommends we increase our knowledge about blockchain as the world is getting more and more complex.
She recommends that we follow bloggers like Brian Krebs on Cybersecurity and Jason Calacanis, a super angel investor that has also written a book about angel investing and start-ups.
Our final question on what furniture Anastassia would be, she responded – a table because it is something to negotiate around, that brings people together, that all businesses are about people and about making all comfortable.
More insights and becoming involved in #AI & #digital
To get more insight into what Anastassia knows and shares, we recommend you explore and build more knowledge of AI, corporate innovation, and governance. We recommend you follow her and some of her recommendations.
On Twitter, you can follow Anastassia @DrALauterbach, Brian Krebs @briankrebs, Jason Calacanis @Jason .
You can also follow the AI thought leaders twitter list we collected
We have also curated a list of a dozen AI podcasts that we recommend for leaders wanting to stay on top of the AI area.
Read more about AI
Explore automation, AI and the future of work in this discussion paper by McKinsey.
Understand more about some of the legal issues and implications in this report by international law firm Hogan Lovells
Learn from other leaders interviewed by Digoshen
You can find inspiration from some of the earlier blog posts and podcasts episodes (Exploring Leaders)
With board members
and leaders of disruptive transformation
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