Generative AI at Workplace | Regenesys

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Artificial Intelligence has been in the news on and off since the best part of last decade. We have seen several reports and experts calling for massive reskilling & loss of work. But have we really seen the impact of AI at work or in our personal life? Perhaps, it is slowly creeping in without us realizing.

Generative AI is the new buzz word. Ever since it made the noise in November 2022, it has taken over our feeds like no other. But is this going to weave into our life like Excel did or will it fade away like Metaverse did?

Leading the Gen-AI Adoption

If a leader is evaluating Generative AI for work, then Data is the critical prerequisite for that consideration. High quality data needs to be available in significantly high quantities and should not be spread across disparate systems. If that litmus test is cleared then we need to build the organizational buy-in and as with any other change management or digital transformation initiatives, it is a huge task. It really puts the negotiation and influencing skills to real test even for a CXO. The usual way, considering the stakeholder pressure as well, is to put together a taskforce and initiate a pilot with key success metrics built in. The key part to note is that the more the workforce engages with Generative AI, the more optimistic they are about using Generative AI proactively and feel less concerned about it.

Gen-AI Adoption

Figure 1: Considerations for a leader

Data privacy and client confidentiality are the top risks that executives have identified in embracing Generative AI through a bard or a ChatGPT. There is enough confusion on how data will be used by the LLM for training or while giving a response to the prompts. If we are smart about it, there are ways to get away with this constraint without compromising the data security and other compliance requirements – if the contract or the company guideline permits it, can we prompt the LLM to recommend the parameters to consider for analysis with the column headings?

Once the above concerns are evaluated & acknowledged and the firm decides to go ahead, there are three approaches that it can take.

  1.   Use open LLM like a ChatGPT or Google Bard
  2.   Use a Tool specific LLM
  3.   Build own private LLM
Type of LLM         Description Remark
Open LLM Open AI, Google and Microsoft offer public LLM whose services are available to all. Their capabilities are nascent but are quickly improving its results every day. Data privacy and confidentiality are key concerns for enterprises in using open LLMs
Tool specific LLM There is a plethora of LLMs available to improve the productivity by automating specific mundane tasks – Midjourney for digital art (marketing) or Crystalknows (Sales) or Fireflies (Meeting notes) These tools require a subscription cost and are relatively inexpensive.
Private LLM Amazon and Google allow organizations to build private LLMs trained with their own data. This addresses many and most of the concerns about privacy & confidentiality.
  • Investment and the associated RoI calculation need to be realistic considering the usecases that the firm has recognized. ChatGPT is estimated to cost over $700,000 to operate a day. 
  • The carbon footprints left behind from training large models run into hundreds of tonnes. The carbon dioxide-equivalent emissions produced by GPT-3 stood at 502 tonnes in 2022[1], the highest when compared to similar-parameter trained models.

Hacking work with Gen-AI

Regardless of the approach one chooses, it is to be remembered that Generative AI, after all, is a tool (technology). The effective utility of the tool is determined by the user. For one to utilize it effectively, he / she needs to know the basics of the tool (prompting), the domain or the functional knowledge and finally the context to apply it. The user needs to be well versed with all three aspects to appreciate and apply the Generative AI tool effectively. Remember that Microsoft Excel was launched in 1985 and in the near four decades, how many of our colleagues know how to use it correctly and effectively. Will Generative AI have a similar path? I hope not.

Hacking work with Gen-AI

Figure 2: Skills Required

According to McKinsey and Gartner, functions such as Sales, Marketing, Customer Service are among the functionalities that contribute to most productivity gains. However, fundamentally, any function which can consume a large amount of text data is ideal – text to text or text to image or text to video generation. Only so far can one go by learning prompting or getting access to the 100s of ‘recommended’ prompts. I believe that only a well skilled and competent individual can be a good prompter.

See the example here: If I were to write a prompt to generate the portrait of an elderly woman, I would probably write ‘portrait of an old woman smiling in her kitchen’. The image on the RIGHT is the result from Clipdrop/Stablediffusion (free version). A professional photographer would perhaps qualify it further like this ‘portrait of an old woman smiling in her kitchen, natural lighting, clear facial features, natural lighting, 35mm, f/1.8, realistic’. Notice the differences here: few of the keywords such as ‘realistic’ are from the prompting world. But the experience of being a photographer in the real world gave me keywords such as ‘natural lighting’, ‘clear facial feature’, and then the lens specs – ’35mm’ and ‘f/1.8’. The professional was replicating the image he had developed in his mind into an art. The differences are evident in the image on the LEFT – the facial features are more real and so are the hands.

portrait of an old woman smiling in her kitchen

Or, consider this example where a management consultant is working with a fast fashion company to reduce carbon footprint. The additional context has made a significant improvement to the response.

Prompt/ Recommend ways to reduce costs across the supply chain while minimizing the company’s carbon footprint for a fast fashion company. Limit response to 200 words.

Google Bard

Prompt/ Write as if you were a management consultant with 10 years of experience working at a global consulting firm. The situation is: your client is the CEO of a global fast fashion company. He is looking for ways to reduce costs across the supply chain while minimizing the company’s carbon footprint. Limit response to 200 words.

Google Bard

Sure, here are some ways to reduce costs across the supply chain while minimizing the company’s carbon footprint for a fast fashion company, limited to 200 words:

  • Use sustainable materials: Fast fashion companies can use sustainable materials, such as recycled polyester, organic cotton, and bamboo, to reduce their environmental impact. These materials require less energy and water to produce, and they can help to reduce the company’s carbon footprint.
  • Optimize transportation: Fast fashion companies can optimize their transportation by using more efficient modes of transportation, such as rail and shipping, and by reducing the distance that products travel.
  • Reduce waste: Fast fashion companies can reduce waste by improving their production processes, such as by using less water and chemicals, and by recycling and reusing materials.
  • Empower suppliers: Fast fashion companies can empower their suppliers to adopt sustainable practices by providing them with training and financial support.
  • These are just a few of the ways that fast fashion companies can reduce their costs and their carbon footprint. By taking these steps, fast fashion companies can play a role in reducing the environmental impact of the fashion industry.
  • Here are some additional considerations for fast fashion companies:
  • Collaboration: Fast fashion companies can collaborate with other businesses, such as retailers, brands, and non-profits, to share best practices and develop new solutions.
  • Transparency: Fast fashion companies can increase transparency by disclosing their environmental impact and their efforts to reduce it. This can help to build trust with consumers and other stakeholders.
  • Accountability: Fast fashion companies can hold themselves accountable for their environmental impact by setting targets and measuring their progress. They can also report their progress to their stakeholders.
  • By taking these steps, fast fashion companies can play a role in reducing the environmental impact of the fashion industry.


Sure, here are some ways to reduce costs across the supply chain while minimizing the company’s carbon footprint:

  • Use sustainable materials: This can help to reduce the environmental impact of the products, as well as the costs associated with waste disposal.
  • Optimize transportation: This can be done by reducing the distance that products travel, using more efficient modes of transportation, and consolidating shipments.
  • Efficient packaging: This can help to reduce the amount of waste generated, as well as the costs associated with packaging materials.
  • Reduce energy consumption: This can be done by using more efficient lighting and appliances, and by implementing energy-saving measures in the manufacturing process.
  • Use renewable energy: This can help to reduce the company’s reliance on fossil fuels, and can also save money on energy costs.
  • Empower employees: Employees can be a valuable resource for identifying and implementing cost-saving and sustainable practices.
  • These are just a few of the many ways that a fast fashion company can reduce costs and its carbon footprint. By taking a holistic approach to sustainability, companies can achieve both environmental and financial benefits.
  • Here are some additional ideas that you can discuss with your client:
  • Partner with suppliers to reduce their environmental impact. This could involve helping them to improve their energy efficiency, reduce waste, or adopt sustainable practices.
  • Invest in research and development to develop new, more sustainable materials and processes. This could lead to long-term cost savings and a reduced environmental impact.
  • Educate consumers about the company’s sustainability efforts. This can help to build customer loyalty and support for the company’s sustainability goals.
  • I hope this helps!


 Prompting works only when the context is clearly defined and when the fundamental understanding is strong. Else, the RoI on the investment on generative AI will be shunted and more by the human here; and we will blame the technology.

Winning in the Extra Time

What is also likely to happen is that Generative AI will free up time for the workforce. What should the management do with the released hours? Instead of exploring options to right-size the workforce, a progressive approach is to either allow employees to have that additional hours for themselves or use the freed-up time for ’employee engagement’ and ‘up-skilling’.

Far too often we have seen how employees find human resources unavailable; HR can spend that much time conversing with the employee. A salesperson can speak to a qualified (& engaged) lead 1-1. OR the time can be well spent on skilling for the future. The generative AI wave is a great opportunity to elevate employees away from routine & mundane tasks and focus on analysis, decision making & meaningful conversations.

The freed-up time also provides a window to support Middle Managers to become better People Leaders. There is often a lack of clarity among their minds with regards to their career progression – do I continue to be in the technical stream, or do I switch to the management stream OR, do I explore unfamiliar roles to extend my competency spectrum? They can be provided with personalized support to develop their people skills and give a direction on their career progression; infact, Generative AI itself can play the role of a personal tutor / coach / mentor for Middle Managers to guide them.  

Skills for implementing Generative AI at workplace.


Awareness Prompt Tool Domain


Senior Management What, Why and How Gen AI can impact business & work Use ‘conversive’ English to ask the right questions to extract the right response     Stakeholder Management

Change Management



Middle Management Leverage use-case specific LLM to drive productivity Refresher People Skills

Career Coach


Junior Management Refresher Mindset
Entry level workforce Refresher


  • The Impact of Generative AI on Manufacturing, Webinar, Gartner
  • How Generative AI is Shaping the Future of Learning and Development, Mark Dearlove
  • Change management considerations when using generative AI in the business, Jack Barnes
  • Benefits of Generative AI in Ensuring Software Quality, Katalon
  • Unleashing developer productivity with generative AI, McKinsey
  • Exploit Generative AI for Happier, More Productive Software Developers, Webinar, Gartner
  • The CEO’s Guide to the Generative AI Revolution, BCG
  • Generative AI’s change management challenge, CIO
  • Navigating Change Management In The Era Of Generative AI, Forbes
  • The next frontier of customer engagement: AI-enabled customer service, McKinsey
  • How Generative AI Is Already Transforming Customer Service, BCG
  • How Generative AI Will Transform HR, BCG
  • AI-powered marketing and sales reach new heights with generative AI, McKinsey
  • Generative AI Will Change Your Business. Here’s How to Adapt, HBR

[1] Measuring trends in Artificial Intelligence, Stanford University

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Adarsh Lathika explores how 'work' as we know will evolve in response to technology and how that will impact the relationship between employer & an employee . He is studying anthropology & neuroscience for its impact in positivity, productivity and wellbeing. He shares his understandings as 'Anatomy of Work' LinkedIn newsletter.

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