Decision points in building an AI-centered organization
by Tobias Straube
The COVID-19 pandemic has triggered a digital transformation at light speed, with AI increasingly taking center stage. According to some estimates, AI is promising to add US$ 4.3 trillion in value to businesses worldwide until 2025.1 And yet, while the potential of AI is widely acknowledged, only half of respondents in a global survey said their organizations have adopted AI in at least one function.2 Other studies suggest that the contrast is even greater in Germany. Although 79% of companies in Germany now consider AI to be very important or critical to their success,3 very few are using AI – 8% to be exact.4 Barriers to higher adoption rates are related to lack of workforce skills, availability of data, identifying and understanding use cases, privacy and cybersecurity implications, and defining vendor strategies.5 And those companies that manage to successfully develop pilots and demonstrate how the use of artificial intelligence will improve their business, often struggle to get beyond the proof of concept stage.6
Meanwhile, the consideration and study of AI ethics, long the subject of discussion in international academic bodies and think tanks, is increasingly finding its way onto the agendas of board rooms. This is not only due to compliance concerns but also strategy-related questions around the company’s values and market positioning in the context of AI. While AI is becoming increasingly important, trust in the digital economy is dwindling. Therefore, the responsible and truly human centred use of AI becomes more important than ever. This is exemplified by the competition between the business models of Apple and Google or Facebook and LinkedIn. On the one hand we see a business model that charges for access to its services in exchange for privacy and the responsible use of tech – think of Apple’s iPhone or LinkedIn’s premium account, and on the other a business model that offers things for free and makes other companies pay for access to their product: The consumer’s behavioural data, see Google or Facebook.
All of this shows that companies that want to get serious about AI need to do more than upgrade their IT departments with data scientists or buy turnkey AI solutions. Harnessing the potential of AI means embarking on a transformation process towards AI-centric organizations. This process involves balancing business and product innovation, aligning business strategies with technology strategies, creating governance regimes, recruiting and developing staff, investing in data availability, accessibility and quality, rethinking the company’s IT architecture and much more.
Join the Show About Strategic decision points for AI in Business w/ Sanjay Srivastava, Chief digital officer at Genpact.
*This show will be post-poned. Please watch this space for an update*
Do you want to find out how to make smart decisions about the best use of AI in your business? Then join the show on (the show has bee post-poned. New date will be announced shortly). The show will be in cooperation with Blockchance Live and we will stream live on YouTube and LinkedIn Live. Be part of the discussion by sending us your questions via Telegram or in the live chat. Find out more about the event here.
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