GenAI Value Varies by Job Function and Industry

Lots of people will choose different words if asked “what is the one word that best describes the value of generative artificial intelligence.” Some might cite “speed” or “scale” or “augmentation” or “automation.” All are applicable.  

At least part of the reason for differing “key value” descriptions is that GenAI arguably has different key values for different job roles and industries. What creates value for illustrators will be distinct from what creates value for software engineers. 

For example, consider GenAI as providing value in a number of different ways. As with all forms of AI, GenAI amplifies some human capability (sight, sound, taste, speech, muscle power, pattern recognition) and therefore amplifies human capabilities within business processes.

That includes:

• Productivity: By automating routine tasks like data entry, report generation, or email drafting, AI frees up human employees to focus on higher-value, strategic work.

• Creativity: It can generate new ideas, design options, or marketing content, acting as a creative catalyst for human teams.

• Decision Support: AI can process vast amounts of data to identify patterns and trends, providing valuable insights that inform better decision-making.

• Customer Experience: By personalizing interactions, generating tailored content, and providing faster responses, AI enhances customer satisfaction.

• Process Optimization: AI can analyze processes to identify inefficiencies and suggest improvements, leading to streamlined operations and cost savings.

So consider a few examples of value created by applying GenAI to creation and innovation; efficiency and productivity; collaboration or the quality of output. 

For marketers, GenAI produces ad copy. For manufacturers, it automates designs or optimizes production processes. Software developers can use it to write code. Customer service agents can offload some queries. 

Pharmaceutical companies can use GenAI in drug discovery operations. 

Industry	Focus of Generative AI Value
Marketing & Advertising	Creation/Innovation (e.g., ad copy, content generation)
Product Design	Quality of Output (e.g., optimizing designs, generating variations)
Manufacturing	Efficiency/Productivity (e.g., automating design tasks, optimizing production lines)
Software Development	Efficiency/Productivity (e.g., code generation, automating testing)
Healthcare	Quality of Output (e.g., drug discovery, personalized medicine)
Customer Service	Efficiency/Productivity & Collaboration (e.g., chatbots, automating repetitive tasks)
Finance	Quality of Output & Prediction (e.g., fraud detection, risk assessment)
Education	Creation/Innovation & Quality of Output (e.g., personalized learning materials, automated grading)
Legal	Efficiency/Productivity & Quality of Output (e.g., legal document review, contract generation)
Media & Entertainment	Creation/Innovation (e.g., scriptwriting, music composition)
Scientific Research	Creation/Innovation & Prediction (e.g., hypothesis generation, data analysis)
Construction	Efficiency/Productivity & Quality of Output (e.g., optimizing construction plans, identifying safety hazards)

The point is that GenAI value depends on the type of industry; its key tasks; as well as job roles within each industry. 

For coders, GenAI allows fast checking of code. In other instances, it is the time saved conducting research that matters. In the pharma industry, it might well be new drug discovery. For content producers the value is mostly in automating content production (producing images, video or text content).