Role of Generative AI in Digital Transformation

Generative AI has revolutionised the stage of technology with the stunning features of ChatGPT. While many businesses are learning to work through the adoption of new-gen AI assistants, many more await their implementation due to a lack of familiarity with the concept. Undoubtedly, AI builds excitement on one end and develops anxiety on the other, which impacts the culture within companies and drives organisational decisions.

Companies that embrace Artificial Intelligence witness its power in making technological decisions more self-healing and the workplace more effective. To integrate business with AI capabilities, leaders should cut through the hype, explore what Generative AI does well and apply these to transform processes, skills, roles, and cultures. Let’s explore the factors that combine the power of Generative AI and digital transformation in detail.

Generative AI refers to AI systems that create new content or data with the help of advanced machine learning techniques. Unlike conventional AI which just analyses data, the generative models engage in the synthesis of the original text, visual media, text, etc. The major examples include advanced language models such as GPT-3, GPT-4, etc., to generate text and stable diffusion to create images.

These models are trained based on massive datasets and tuned to create custom outputs. Businesses can dive into the vast potential of Generative AI to resolve complicated challenges. Through generating human-quality content and insights, generative models behave as digital assistants for enterprises to ace the digital transformation journey.

Broadly speaking, AI, or Artificial Intelligence is the research towards developing computer systems to automatically implement the tasks that are normally implemented with human capabilities. This includes visual perception, speech recognition, decision making and language translation features.

Generative AI is a subset of Artificial Intelligence that depends on Machine Learning, the classification of data science that builds AI models and uses data patterns to learn with no need for human direction.

The continuous generation of massive amounts of data in large quantities and varieties across businesses is propelling advancements in Machine Learning. Generative AI is one such advanced technology that incorporates an algorithm-specific system that takes autonomously trained action on input data.

Unlike conventional AI, which is highly utilised to categorise data, Generative AI generates output like computer code, text, images and audio based on the training datasets. Generative AI tools help systems produce outputs that depend on futuristic patterns in response to queries. For instance, conventional AI could be useful in identifying artefacts in mammogram images that uncover hard-to-detect cancers.

Generative AI could be prompted and trained to generate new images with similar artefacts and false positive artefacts to let medical students find out what they should look for while reviewing mammogram images.

Generative AI has captured the attention of both the executive suite and the public. IT and data leadership should anticipate business leaders bringing up Generative AI for discussion and implementation since it is going to be a breakthrough.

AI has a large number of benefits, however, maximising those benefits demands extensive expertise. Here are the four core considerations that businesses need to look for while strategically collaborating with their AI partner. 

• High-end skills and expertise: Having a keen eye for detail on how to capitalise on AI opportunities is one of the core areas. The AI partner should highlight technical expertise, industry-specific skills, and a history of success.
• Training and Support: A perfect AI partner should offer holistic training programs to enable knowledge transfer to the team and make sure they can manage and understand the deployed AI systems. 
• Collaboration for AI potential: With effective collaboration, an ideal AI partner acts as an integral part of successful AI integration for smart processes.
• Foster Scalability: The partner should also support customising solutions to build particular business outcomes for the enterprise and integrate with the existing systems for a seamless process.

With the right AI and ML development company, you can adopt the right ecosystem for the business and implement all the necessary AI-related processes, propelling innovation for a digital transformation. 

Generative AI models are on their way to scaling up businesses, and here are the major areas of application where you can implement the features of AI in digital transformation:

Marketing & Sales: Targeting personalised marketing, social media, technical sales content, and developing assistants for particular businesses like retail.
Operations: Creating task lists to ensure efficient execution of a particular activity.
IT/Engineering: Generating, documenting and reviewing codes. 
Risk and Legal Applications: Answering complex queries, pulling out huge amounts of legal documentation, and producing and reviewing yearly reports.
Research & Development: Triggering drug discovery with a high understanding of diseases and discovering chemical structures.

Marketing Applications

These generative models are potentially significant across various business functions. A marketing-focused version of GPT can help generate blogs, web copies, social media posts, ads, sales emails, and various other customer-facing content. It fine-tunes the GPT models with the outputs of customers, making the campaigns and copies the most effective. Using Generative AI capabilities for marketing strategy can be the best method to make advertising campaigns efficient. For example, Stitch Fix is a clothing company that takes the help of AI to recommend particular clothing to customers and experiments using DALL-E 2 to produce visualisations of dressing depending upon the customer preferences for style, fabric, and colour.

Code Generation Applications

GPT-3 has been an ideal generator of program code. Though not perfect as a human coder, GPT-3’s Codex program is specifically trained to ace code generation. With a snippet or small program function, it produces output in a wide variety of languages. Microsoft’s Github has another GPT-3 version to improve code generation, which is called ‘CoPilot’. The advanced versions of Codex can now detect bugs, fix them in their code, and define what the code does. The key objective of Microsoft is not to eliminate human programmers but to implement more tools, such as pair programmers, to help humans improve speed and effectiveness.

Conversational Applications

Generative AI places a keen focus on conversational AI and chatbots. They offer high levels of understanding of conversation and build necessary context awareness compared to the existing conversational technologies. For instance, Google’s BERT is a good option for understanding search queries and is also an element of the DiagFlow chatbot engine of the company. LLM is the right conversationalist. By training them on past human content, they tend to replicate any biased, racist or sensitive language in the existing data. These are under training and making efforts to filter out hate speech in the future.

Knowledge Management Applications

One major application of LLM is using it as a means to implement text-image or video-based knowledge for businesses. The labour of helping to develop structured knowledge bases has left little room for knowledge management. However, based on some research, LLMs can be effective at managing an organisation's knowledge, while model training is optimised based on a specific body of text-specific knowledge in the organisation.

Generative AI is a transformative technology that redefines the digital segment and scales the digital revolution efforts across industries. Businesses that leverage the positive implementation aspects of Generative AI in digital transformation can cultivate significant advantages. As Generative AI continues to evolve, this plays a crucial role in shaping the future of business.

Organisations need to explore their potential and integrate AI and digital transformation strategies in their business to ensure they stay ahead in the ever-evolving technological ecosystem. Being the most recent frontier in the segment of artificial intelligence, the full-fledged capabilities of Generative AI are yet to be unveiled.