Pankaj Kedia’s Post

The latest Wharton-GBK Collective study on GenAI adoption reveals a seismic shift in workplace technology integration, with weekly usage projected to nearly double across most departments by 2024. The data suggests we're witnessing not just incremental change, but a fundamental transformation in how organizations operate, with traditionally conservative departments like Legal and Procurement showing surprisingly aggressive adoption trajectories. What's particularly fascinating is the correlation between current adoption rates and perceived impact. Departments with early adoption, such as IT and Business Intelligence, report the highest positive impact (89% medium to high), while also maintaining the highest weekly usage rates. This suggests a powerful feedback loop where experience with GenAI drives both confidence and expanded implementation, potentially creating a widening capability gap between organizations that embrace these technologies and those that delay adoption.s we stand at this inflection point in organizational evolution, one must wonder: Will the rapid adoption rates we're seeing create a new digital divide between AI-native and AI-hesitant organizations, fundamentally reshaping competitive dynamics across industries? My opinion of the top three most impactful observations: 1. The IT/Business Intelligence sector shows both the highest current adoption (66% in 2023) and perceived impact (58% high impact), indicating a clear technological vanguard in GenAI implementation. 2. There's a dramatic projected increase in GenAI usage across all departments from 2023 to 2024, with Purchasing/Procurement showing the most aggressive growth (from 50% to 94%), suggesting a transformation in how organizations manage their supply chains and vendor relationships. 3. Despite being heavily regulated, Legal departments show the lowest current adoption (16%) but anticipate significant growth (69% by 2024), reflecting a careful but decisive shift toward AI integration in legal operations. #GenerativeAI #FutureOfWork #DigitalTransformation #BusinessStrategy #AIAdoption #Leadership #WhartonInsights #EnterpriseAI

How to Accelerate AI Adoption: 3 Non-Obvious Takeaways from AI at Wharton’s AI Adoption Report   1.    EXCESSIVE GOVERNANCE MAY BE THWARTING ADOPTION AT LARGER FIRMS Here’s why: while 51% of all companies have few or no AI usage restrictions, this drops dramatically to just 27% among $2B+ companies. Yet these larger companies also report significantly lower weekly AI usage (48% vs 80% for smaller firms). The root cause? The AI policies of these large organizations, as Ethan Mollick previously reported in his blog, One Useful Thing. Why? They emphasize the dangers of AI and penalize incorrect use. The result? Fewer employees use it. New behaviors need social proof, that scientific truth that says that in times of uncertainty, we look to the behavior of others to know what to do. If large organizations want to stay ahead, their organizations need visible evidence that others are using it. They should consider revising AI policy and giving all employees access to paid versions of foundational models. 2.    STARTING SMALL SPEEDS ADOPTION Adoption was driven by small-scale, productivity saving tasks like document summarization (64%), data analysis (62%) and meeting notes (59%). These are low-risk, gateway use cases where employees can quickly see success, building confidence for more complex initiatives. Any time we start something new, we need to know that we can succeed. (Self-Efficacy Principle). We start small to guarantee success. These quick wins from early adopters then reduce the risk that paves the wave for adoption by subsequent users. That's why big gains in adoption were accompanied by increases in user sentiments, like Pleased and Excited, and decreases in sentiments like Caution and Skepticism. Starting small also avoids the resistance that occurs with big changes. The bigger the change, the higher the risk of failure, the greater the resistance. And what happens with an early failure? Your ability to get widespread organizational support for future initiatives is compromised. 3.    MUTUAL MENTORING COULD SPEED ADOPTION Given the sizeable age-related usage gap (80% for 18-34 vs 42% for 55+), consider programs where younger, AI-proficient employees mentor senior leaders. Senior leaders often resist new technologies because they fear losing status by appearing incompetent. In a private mentoring relationship with a younger colleague, they can learn without public vulnerability. Senior leaders in turn can provide younger employees with the subject matter expertise and judgment that enhances THEIR AI expertise. Technology adoption happens fastest in an organization through a "both-ends-to-the-middle" approach, endorsed and used by senior leaders and workers at the ground level.   It’s a great report and worth digging into. I’m highlighting just 3 non-obvious insights that could help your business.

Today we are proud to unveil a new study conducted by #AIatWharton and GBK Collective that assesses the rate at which companies are adopting generative AI into their workplace, while also charting the sentiment of workers towards AI over a one-year period. The study – which surveyed more than 800 senior business leaders – finds that weekly AI use has nearly doubled since 2023, and investment by companies has jumped 130%. You can access the full report – written by Stefano Puntoni, Mary Purk, and Jeremy Korst – at the link below: https://lnkd.in/eZSaegT7

I’m excited to unveil our 2024 follow up to last year’s AI adoption at work study! Our study, encompassing insights from over 800 senior leaders from top U.S. enterprises (each boasting sales over $50M), shows just how rapidly Gen AI adoption and use cases are accelerating. Key Findings:  - Nearly 3 in 4 leaders (72%) report using Gen AI at least once a week, up from 37% in 2023.  - AI adoption by Marketing and Sales leaders tripled, from 20% to 62%, with usage by Operations, HR, and Procurement doubling.  - Spending on AI has increased by 130%, with 3 in 4 companies planning further investment in 2025.  - 9 out of 10 leaders agree that AI enhances employee skills, up from 80%, while concerns about job replacement have eased.    Our study also highlights the shift from experimentation with Gen AI to realizing tangible ROI as companies deepen their integration of AI across areas. I had tremendous fun working with and learning from my co-authors Prof. Stefano Puntoni, professor of Marketing at The Wharton School and co-director of AI at Wharton, and Mary Purk, executive director of AI at Wharton. Also huge thanks to our GBK Collective project team Brian Smith, Daniel Urbina-McCarthy, Amelia Francesca Colón, and David Henderson, as well as the Wharton AI & Analytics Initiative team.

I know many of you are using ChatGPT and other Gen AI tools to help get more done at work, or at least to spend less time working. For anyone interested in the adoption of these tools, I highly recommend checking out the in-depth study "Growing Up: Navigating Gen AI's Early Years," recently released by GBK Collective in partnership with the Wharton AI & Analytics Initiative. This report provides a detailed summary of Gen AI adoption, current sentiment, and future prospects among industry executives—and it might just give you a few ideas for how to implement these tools yourself. Stayed tuned for our follow-up study focused on Gen AI adoption among market research and insights professionals, which includes research on the use of synthetic data and other "hot topics".

The potential for GenAI in Public Service is significant. Accenture research shows that 42% of all working hours in public service globally are in scope for augmentation or automation through generative AI. This blog by my colleagues highlights the potential AND the dual role of public service in making sure all can reap the benefits.

Public service workers are more optimistic than their peers in other industries about the impact of generative AI on work. Leaders need to leverage this positive outlook and provide personalized upskilling and training programs to prepare their workforce for the future. Check out this blog by Accenture's Natalie J. Sisto and Rainer Binder that highlights how public service organizations can embrace the opportunities from AI and create a better work environment. #GenerativeAI #Workforce #PublicService 

I love the themes in this blog on the dual role government plays in helping ensure its own workers, and the labor forces it serves, are equipped with the right skills to thrive in an era of generative AI. #GenerativeAI #PublicService #Workforce

75% of public service organizations lack comprehensive strategies to harness the positive outcomes of generative AI. It's time to act and redesign workflows, improve the allocation of a scare skilled workforce and foster cross-functional collaboration to drive greater operational efficiency. Read more in this blog by Natalie J. Sisto and Rainer Binder #GenerativeAI #Operations #PublicService

Global view of how #GenAI is continuing to transform public service agencies and the broader #workforcedevelopment and employment services ecosystems.