What is Generative AI? 

How does Gen AI differ from traditional AI? The primary difference between traditional AI and Gen AI is that the latter can create novel output that appears to be generated by humans. The coherent writing and hyper-realistic images that have captured public and business interest are examples of Gen AI models outputting data in ways once only possible with human thought, creativity, and effort. Today, Gen AI models can create outputs in multiple modalities:

• Text – Written language outputs in an accessible tone and quality, with details and complexity aligned with the user’s needs, such as summarizing documents, writing customer-facing materials, and explaining complex topics in natural language.
• Code – Computer code in a variety of programming languages with the capacity to autonomously summarize, document, and annotate the code for human developers.
• Audio – Output in natural, conversational, and even colloquial styles with the capacity to rapidly shift among languages, tone, and degrees of complexity. Examples include Gen AI-powered call centers and troubleshooting support for technicians in the field.
• Image – Create images with varying degrees of realism, variability, and creativity. Examples include simulating how a product might look in a customer’s home or reconstructing an accident scene to assess insurance claims and liability.
• Video – Similar to imagery, Gen AI models can take user prompts and generate videos, with scenes, people, and objects that are entirely fictitious and created by the model, such as autonomously generated marketing videos to showcase a new product.
• 3D/Specialized – From text or two-dimensional inputs, models can extrapolate and generate data representing 3D objects. Examples include creating virtual renderings in an omniverse environment and AI-assisted prototyping and design in a purely virtual space.

How can it improve my business?

With a remarkable capacity to consume and generate information in different modalities, Gen AI has unleashed new ways of working and transforming enterprises across every sector.

Through its collection of business-ready Gen AI industry use cases and applications, Deloitte outlines various advantages of Gen AI in driving efficiency, creativity, speed, scale and capacity and highlights modalities and considerations for risk and trust: 

• Financial services – The potential value of Gen AI in FS is not merely a downstream application, but rather it can serve as a powerful and complementary tool working with developers, and other machine learning models and applications. Integrating Gen AI into an FS organization’s wider technology stack can support documentation automation, help banks personalize financial advice for customers based on their spending habits and goals, and help convert unstructured information from old documents into structured, actionable data.
• Technology media and telecommunications – The data-rich TMT industry sees its greatest potential Gen AI value in can optimize customer service by using chatbots that understand and respond to user queries with human-like accuracy, or triage incoming calls and emails for further processing. It can also assist in content creation, such as writing code for new software or generating articles for media outlets, freeing up human talent for more strategic tasks. 
• Energy and utilities – Faced with substantial challenges related to energy security, affordability and profitability, energy and utility companies can use Gen AI to glean valuable insights from their existing data, or generate code to simulate complex systems. Looking to the future, Gen AI will play a central role in developing real-time, bespoke training materials to support the workforce through transition and adoption of sustainable practices.
• Consumer – For businesses in the consumer sector, Gen AI holds vast potential for improving and enhancing interactions, creating compelling content on demand, and analyzing consumer feedback to identify trends and inform product development, ensuring that new offerings meet market demands. From helping customers find the answers and products they need to enabling a level of market analysis with granularity and speed that was previously unachievable, Gen AI will sit at the core of consumer business.
• Government and public services – GPS organizations are increasingly exploring how Gen AI can be used to help automate administrative tasks, analyze policy documents, parse case notes, and inform customized citizen services. In fulfilling their duty to serve their constituents, public servants can use Gen AI and natural language processing to revolutionize the way governments understand and interact with citizens while promoting the responsible use of this technology.
• Life sciences and health care – Gen AI can help transform the LSHC sector in three archetypical ways: enhancing operational performance through improved employee productivity; providing hyper-personalized experiences to patients, customers, and employees; and developing enterprise digital and data solutions. Together, these capabilities have the power to improve efficiency, experience and agility and enhance quality of care and health outcomes. 

We recommend starting your journey with a facilitated Deloitte Gen AI Activation Lab.

• This set of workshops and maturity assessment will help kick-start the Generative AI journey for your organization. The Gen AI Activation Lab explains the shift from automations to AI and helps your team understand the criteria for selection of processes suitable for hyper-automation.
  
• As a next step we typically continue with the Scaling Lab, a set of workshops and exercises that help identify concrete use cases and implement the PoC in your environment to give you the first success. 
• Once your team becomes familiar with the Gen AI contribution from the initial MVP implementation, we can proceed to the next phase, embarking on a transformation project that will fully onboard your team and organization into the new technology and re-imagine the processes.