Draup was invited to present at the Conference Board this week.  I presented the granular workload repercussions of Generative AI on key operational domains like Finance, HR, Supply Chain, and analogous functions.  The audience showed considerable enthusiasm by exploring distinct scenarios where Generative AI can create significant value, including tasks such as generating initial interpretations of financial statements, drafting initial versions of legal contracts, compiling comprehensive lists of tools for specific migration plans, and much more.

Here are the top concerns/questions the group raised and our associated responses.

• Will my proprietary data become accessible to others?  The top concern is establishing guard rails so that the proprietary data is not accessible to others.  Very recently, Samsung has expressed concern and said one of the staff uploaded sensitive code to ChatGPT during the development process.  Such concerns exist widely in the industry though we are optimistic that these aspects will get better very soon (ChatGPT is already bringing out an incognito mode if you do not want your data to be used by their ML models)
• How will this impact headcount?:  While it is unclear how the models and processes will impact headcount, some efficiency measures are becoming evident through the pilots.  In contact centers, efficiency measures up to 30 to 40% are reported as it significantly cuts down navigation time, extracting data from several systems.  This problem is also a problem that call centers have been attempting to solve for a while
• Many vendors of existing products are claiming they have Gen AI solutions.  How do we understand this?: Many vendors are enabling a conversational Chatbot on top of their existing data sets.  This aspect may not be fully done, and different vendors will be at different stages of development.  Vendors are also under a lot of pressure to showcase something, so we have to evaluate this on a case-by-case basis
• AI Safety and Bias:  During the session, there was a notable influx of inquiries revolving around AI bias and safety.  Attendees expressed keen interest in understanding the measures taken to address and mitigate bias in AI systems, as well as the steps taken to ensure the safety and ethical implications associated with the deployment of Generative AI technologies.  Discussions addressed the importance of robust training data, algorithmic transparency, fairness, and accountability to build AI systems that are unbiased, secure, and reliable.  Participants were eager to explore best practices and emerging research in this field to foster the responsible and trustworthy implementation of AI technologies.

Our primary focus of discussion revolved around empowering existing roles to acquire new skills and broaden their horizons in light of the evolving work landscape.

Here are some specific examples of what we discussed (only representative and not exhaustive)

Recruiters: 

• Employer Branding Science – Brand Consistency, EVP, Social Media Presence, and several skills belong here
• Understanding machine-written resume patterns
• Understanding the types of bias in selection
• Deeper peer organization knowledge (nuanced knowledge of specific orgs working on specialized projects/products)

Workforce Planners: 

• Deeper analysis of developing demand assumptions (thus far, Demand is taken as an assumption given by the business, and this will change),
• Understanding Sustainability modeling
• Efficiency Ratios for Generative AI assumptions

The following table gives an outline of the various new skills that were discussed in the room.  I have given a representative set of functions, as there were several functions discussed

As workforce planning embraces the integration of human-machine combinations for executing workloads, we may witness the emergence of smaller ecosystems to facilitate this synergy.  We analyzed Greece recently and mapped out innovative talent in the tech and science sectors.  With technologies like ChatGPT, these locations may come into prominence as a choice to establish smaller to medium headcount innovation hubs.  This aspect is another possible shift in location strategies due to Generative AI.