How Generative AI is redefining work and catalyzing innovation

Generative AI is revolutionizing the way we work and igniting innovation across various industries. By harnessing the power of machine learning, generative AI systems are capable of autonomously creating new and original content. This automation not only accelerates the creative process but also reduces the burden of manual effort. Rahul Lodhe, Senior Director, SAP Artificial Intelligence, spoke to Dataquest on the occasion of AI Appreciation Day to shed more light on this. 

DQ: What is your perspective on the future of AI? How will generative AI change the way we work

Rahul Lodhe: The future of AI is expected to be transformative and impactful across various industries and aspects of our lives. AI technologies have the potential to revolutionize healthcare, transportation, manufacturing, finance, and many other sectors. They can improve efficiency, accuracy, and productivity, leading to significant advancements.

In the coming years, we can expect AI to continue to evolve and become more sophisticated. Deep learning models, Large Language models have already demonstrated remarkable capabilities in natural language processing, image recognition, and other tasks. As research progresses, we can anticipate even more powerful AI systems that can handle complex tasks, reason, and understand context more effectively.

With such high pace advance in AI, we may eventually develop Artificial General Intelligence (AGI) — a type of AI that can understand, learn, and apply its intelligence to any intellectual task that a human being can. However, this is a contentious topic and there's no consensus on when or even if AGI will be achieved.

Generative AI will revolutionize the way we work by automating and enhancing numerous tasks. It can generate creative content such as articles, music, or designs, thereby accelerating innovation and reducing manual   effort. For customer service, AI can draft emails or chat responses, improving efficiency. In programming, AI can write or debug code, reducing development time. In decision-making, AI can generate multiple scenarios to aid strategic planning. It will also democratize expertise, as AI models trained in specific domains can provide insights and advice, making specialized knowledge accessible to non-experts.

However, there are also concerns about the ethical implications of AI. Issues such as privacy, bias, job displacement, and the potential for misuse need to be carefully addressed. It is crucial to ensure that AI systems are developed and deployed responsibly, with proper regulations and safeguards in place.

Overall, the future of AI holds immense potential for positive change, but it also requires responsible development and deployment to mitigate potential risks and ensure the technology benefits society as a whole.

DQ: How are you skilling your employees to develop and work with generative AI?

Rahul Lodhe: As Generative AI is a fairly new area and possibilities of application is quite wide compared to Narrow AI. In case of Narrow AI the upskilling was limited to certain level of technical or expert functional roles ex data scientist, ML engineers etc BUT in case of GenAI target upskilling requirement is across the organisation with focus on doing good prompt engineering to generate desired outcome based on huge pre trained model with billon of parameters hence applicability of upskilling applicable for all the roles in organization ex. developers, QA, User Assistance , HR , Finance etc.

As the GenAI is nish and quite evolving topic the upskilling hence needed multifield approach:

• At SAP Labs India, we started Generative AI User group with about 2500 AI enthusiast to hold regular session on GenAI and possible adoptable usecases across various business functions.
• Specific learning days focus only on GenAI upskilling
• Curated GenAI training program for specific role
• Regular Hackathon to bring up GenAI use cases across business functions and developer efficiency

DQ: What are the ethical considerations while using generative AI and how do you ensure an ethical implementation of AI and automation?

Rahul Lodhe: I believe that Artificial Intelligence has the potential to unlock boundless potential for businesses, governments, and society. Concerns about AI often stem from unanswered questions and uncertainty about whether autonomous systems can be used fairly, responsibly, transparently, and in compliance with data protection and privacy regulations. Governing AI requires clearly defined rules, values, principles, and techniques to guide the responsible development of AI systems.

SAP AI abides by the highest industry standards on responsible AI. For years, we have been working with leading ethics experts as part of SAP's AI ethics advisory panel to explore the implications of deploying AI in the enterprise.

SAP’s Global AI Ethics Policy serves to define the intent, expectations and instruction for AI Ethics at SAP and translates our Guiding Principles into practice. The policy applies to SAP and its employees worldwide involved in the development, deployment and sale of SAP developed AI systems. The policy consists of three pillars:

• Human Agency and Oversight sets out requirements for human oversight and the appropriate governance mechanisms, to safeguard human autonomy, particularly for automated decision-making.
• Addressing Bias and Discrimination sets out the requirements to avoid marginalization, inequality, and discrimination in data sources and models that otherwise may exist in society, so that SAP-developed AI systems do not generate unfairly biased results.
• Transparency and Explainability sets out the requirements to provide transparency in both the development process of AI systems as well as decisions taken by AI systems.

DQ: Can you elaborate on some use cases for generative AI?

Rahul Lodhe: The Generative AI would be bring the art of the possibility in many ways, its evolving every day. Based on current capability GenAI with it would applied for Enterprise application in the following ways.

SAP has already announced following Generative AI use cases will be part of products during SAPPHIRE 2023 event:

• SAP SuccessFactors: Job description & interview questions generation
• SAP Transportation Management: Goods receipt processing
• Sales and Services
• SAP Digital Assistant for CX : ​Intelligent questions & answers, Customer 360 profile summary & Scheduling assistants
• Marketing and Communication : Natural language marketing analytics, Product description generation & review summaries
• SAP Analytics Cloud: Natural language queries
• SAP Signavio Process Manager: Process model generation and documentation 
• SAP Digital Assistant: Product documentation search
• GPT-based CAP (Cloud Application Programming) model & data generation  

The possibilities are many and just state a few more additional use cases:

 Improve software and service experience of customers

• Interactions with software using natural language
• Automation in customer support

Conversational retrieval of information

• Assist content creation and knowledge management
• Generation or improvement of e.g., marketing and sales copies and other content
• Summarization of documents and data

Increase speed and effectiveness of developers

• Code-generation from natural language as well as code auto-completion
• Automated generation of documentation.