- Decentralized AI Adoption: An argument for distributing ownership of AI processes among teams instead of centralized control under a single executive.?
- Gen AI Talent Landscape & Productivity: McKinsey highlights a broad pool of gen AI talent, with 88% of respondents in non-technical roles using gen AI.?
- AI Research Race: China surpasses U.S. in leading AI research in over half of hottest AI fields according to Georgetown University's CSET research.?
Teams Should Drive AI Adoption
An article
by Sowmyanarayan Sampath, CEO of Verizon Consumer, expands on the benefits of distributing ownership of AI processes among teams.?
- The widespread adoption of Generative AI across various business sectors prompts leaders to consider centralized control under a seasoned executive.?
- However, appointing a designated senior leader ("czar") for new technologies like AI is often a mistake, as observed in past instances such as with the metaverse and blockchain.?
- Leaders should encourage innovation to occur at the frontline level, allowing teams to own the process and adapt technology to workflows.?
- Ex. Verizon's approach involves decentralized decision-making, with teams close to the work owning AI implementation and providing real-time feedback.?
- AI application areas at Verizon include operations, network optimization, customer care, and sales, with a focus on relieving cognitive load and improving efficiency.?
- By leveraging AI tools, Verizon has seen improvements in answer accuracy rates, sales conversion rates, and overall customer satisfaction.?
- The success and failure of AI initiatives at Verizon are not centralized under a single executive but are owned by empowered frontline stakeholders.?
While companies should have a clear vision for AI adoption, success ultimately relies on empowering frontline employees to drive operational excellence.?
Understanding Productivity Alongside Gen AI
A McKinsey survey revealed that the pool of gen AI talent is broader than anticipated, with 88% of respondents in non-technical roles using gen AI for rote tasks.?
- Despite the demand for gen AI talent, 51% of heavy users and creators plan to quit their jobs in the next three to six months, emphasizing the need for better retention strategies.?
- Heavy users and creators prioritize flexibility and relational factors over pay, highlighting the importance of meaningful work and supportive work environments.?
- Workers using gen AI increasingly prioritize higher-level cognitive and social-emotional skills, recognizing their importance for handling repetitive tasks effectively.?
- Employers tend to aim for internal development of gen AI talent, but retaining employees who plan to leave presents a challenge.?
- The gap between what employees want in a job and what employers offer highlights the need for a people-centric approach to talent strategy.?
- Gen AI can enhance productivity and automation, but leaders must consider redefining jobs to be more human-centric, redefining flexibility, and emphasizing active listening to address workforce concerns.?
Companies that prioritize human skills and create fulfilling work environments are likely to see higher performance and employee loyalty in the long term.?
?? From the Web?
The 2024 Work Trend Index by Microsoft and LinkedIn reveals AI's widespread adoption at work, urging leaders to move from experimentation to tangible business impact.?
OpenAI plans a ChatGPT feature to search the web, cite sources, and provide answers, potentially competing with Google and Perplexity.?
?Private equity and asset managers gear up for significant M&A and investments in Asia Pacific data centers, driven by AI demand, leading global dealmaking.?
China, USA in the Race for AI Research
According to research
from Georgetown University's Center for Security and Emerging Technology (CSET), China surpasses the U.S. in leading AI research in more than half of the hottest AI fields.?
- Global AI research doubled between 2017 and 2022.?
- Computer vision accounts for 32% of AI research, growing by 121%.?
- Natural language processing represents 11% of AI papers, growing by 104%.?
- Robotics research grew slower at 54% and comprised 15% of AI research.?
- AI safety research, despite growing by 315%, only constituted 2% of all research.?
- Federal investment in basic measurement evaluation for AI safety is deemed crucial.?
- Chinese institutions dominate in sheer numbers of AI research papers, with the Chinese Academy of Sciences leading.?
- Highly cited papers still see the Chinese Academy of Sciences as the leader, followed by Google, Tsinghua University, Stanford, and MIT.?
- The U.S. leads in highly cited articles at the country level.?
- Google and Microsoft lead in natural language processing research.?
- China excels in computer vision research, with Tsinghua University as the top organization.?
- China's strategic AI priorities include autonomous vehicles, manufacturing, and surveillance.?
- India, particularly Chitkara University, is noted for AI applications in plant disease detection.
?? Prompt of the week?
Act as a sentiment classifier. Classify the following text which came from [describe text origin] as “positive”, “negative”, “neutral” or “unsure”: [Insert text to be classifier].
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