How to land and expand on Generative AI capabilities

Authors

Anurag Sahay

The Managing Director & Global Business Unit Head- AI and Data Sciences at Nagarro. He is strategically and technically leading the Generative AI segment, minimizing the risk and maximizing its impact for the clients.

Avantika Kaushik

Avantika Kaushik is a strong communicator with expertise in taking technology to the masses and businesses.

Highlight:

The capabilities of Generative AI are blowing people's minds, with business leaders taking a head start and legal brains getting into discussions. CEOs are calling the shots by deciding to be among the first ones to reach out for Generative AI-based business opportunities.  
 
The early report on these pilots is that there are risks and challenges, but the value-opportunity vastly outweighs the risks and challenges. Its outcomes have strengthened supply chains, built sustainable practices, and opened multifaceted, Generative AI-based value chains. 
 
There is an urgency among businesses to plunge into business reinvention. Everyone wants to snap up on Generative AI's economic and functional potential. But the truth is that we are only halfway there, as Generative AI is still growing, so it should only be adopted in well-thought-out use cases. We will discuss the pace, capabilities, and opportunities in Generative AI. We will also suggest how to build your strategic edge to be at the forefront while avoiding risks.

AI is not new; we have been connecting dots with AI for quite some time. It gradually infused itself into our lives through— smartphones, autonomous automobiles, and technologies used by merchants to surprise and delight customers. But its advancement was essentially unnoticeable. The release of ChatGPT last November (2022) changed the AI game and brought a whole new level of disruption and related opportunities. 

ChatGPT was ready by August-September 2022. However, research companies tested it for six to seven months, solving its alignment problem with human values. According to a report released by Sparks of Artificial General Intelligence (Sparks AGI), researchers went through different qualities of intelligence: reasoning, planning, thinking abstractly, solving complex problems, understanding the theory of mind, and other things, and the results were groundbreaking. They found dramatic outcomes of this test as GTP shattered the benchmark.  

“In our exploration of GPT-4, we emphasize discovering its limitations, and we discuss the challenges ahead for advancing towards deeper and more comprehensive versions of AGI, including the possible need for pursuing a new paradigm that moves beyond next-word prediction. We conclude with reflections on societal influences of the recent technological leap and future research directions.” (Source: Sparks of Artificial General Intelligence).   

Quite as expected, Generative AI’s adoption exploded, with over 100 million users within two months of its launch. According to a report by Statistica, value in the Generative AI market is projected to reach US$0.76bn in 2023; showing an annual growth rate (CAGR 2023-2030) of 27.65%, resulting in a market volume of US$4.20bn by 2030. 

However, Generative AI adoption shouldn't be seen as a goal in its own right. A business leader must map the adoption with business growth to achieve economies of scale. Build a path, dotting it with shorter goals of process optimization, functional efficiency, business insight, economic expansion, and higher productivity.

Generative AI’s capabilities

One question that has been doing the rounds is: how does Generative AI differ from other AI? What more value can it possibly bring?

While AI works by detecting patterns in data and using them to make predictions and decisions, Generative AI produces fresh and seemingly original content for chats and designs. It even produces synthetic data and carries out sophisticated conversations with users. The results have a higher level of intricacy, like a high-resolution image, and an intriguing new component. Generative AI covers a wider range of modalities, such as text, imagery, music, code, and voices, becoming an unstoppable force.  

According to Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence, published by Working Paper by Shakked Noy and Whitney Zhang- MIT (March 2, 2023): 

“Our results show that ChatGPT substantially raises average productivity: time taken decreases by 0.8 SDs and output quality rises by 0.4 SDs. Inequality between workers decreases, as ChatGPT compresses the productivity distribution by benefiting low-ability workers more. ChatGPT mostly substitutes for worker effort rather than complementing worker skills, and restructures tasks towards idea-generation and editing and away from rough-drafting. Exposure to ChatGPT increases job satisfaction and self-efficacy and heightens both concern and excitement about automation technologies.” 

Human productivity is set to scale to new levels.

GenAI's Functional Potentials

“We are at the beginning of an AI revolution, which will touch every organization, every product and service, and person on earth” Anurag Sahay.

As businesses scout the full potential of the technology, they also need a more formal approach to unlock its value. A strategic move will keep you abreast of the related complications & risks and achieve the desired results.

Reinvent operations, selectively & gradually

The recently released report the- The economic potential of Generative AI The next productivity frontier by Mckinsey & Company affirmed why all the businesses needs to start reinventing functions: 
 
“Generative AI’s impact on productivity could add trillions of dollars in value to the global economy. Our latest research estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases we analyzed—by comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion. This would increase the impact of all artificial intelligence by 15 to 40 percent. This estimate would roughly double if we include the impact of embedding generative AI into software that is currently used for other tasks beyond those use cases.” 
 
Backing this up, New York Times published “McKinsey had previously predicted that A.I. would automate half of all work between 2035 and 2075, but the power of generative A.I. tools — which exploded onto the tech scene late last year — accelerated the company’s forecast”.  

Reinventing operations gradually is essential but where to start from?

We must be responsible in handling Generative AI by deciding our approach to solving a problem. It can be adopted in two ways; first, its adoption can be broad, including several aspects of value creation across departments. Second, it can be a strategic adoption where an organization isn’t looking to implement several use cases but rather focuses on two or three important areas where Generative AI can drive difference for them. Identifying the approach is critical, which makes it essential to take thought-out steps ahead. 

Productive opportunity in Generative AI

It is primarily four areas that make up around 75% of the potential value Generative AI use cases could provide: Customer operations, sales, and marketing, programming, and R&D.  (Source: McKinsey). Here is a look at the effect of Generative AI on productivity across functions.   

Business value Generative AI can build

1. • GenAI in software engineering

   Generative AI as a developer’s coding assistant will help them maximize productivity with its coding tools’ distinct advantages for developer workflow.

2.  

   • GenAI in customer operations

   Independent of the consumer's language or location, chatbots powered by Generative AI can respond to difficult customer inquiries right away and in a personalized way.

3. Also, it enables customer care teams to handle inquiries that can only be answered by a human agent. Generative AI can automate responses to a bigger percentage of customer inquiries by improving the quality and effectiveness of interactions via automated channels.   

4.  

   • GenAI in marketing & sales

   Generative AI revolutionizes marketing and advertising with its ability to produce highly customized content for consumers. AI-driven algorithms create customized marketing messages and campaigns by examining consumer data and preferences, dramatically increase customer engagement and lead conversions.  

5.  

   • GenAI in product testing (R&D)

   Rapidly producing candidate designs increases productivity, also improving the designs. This saves production and logistics costs.

6. Additionally, it enhances product testing and quality, which through its capacity to create scenarios and conduct profile testing, can assist in shortening the testing period for complicated systems and speeding up the trial phases, including customer testing.  

7.  

   • GenAI in administrative tasks

   With the help of Generative AI, administrative teams can automate time-consuming, repetitive administrative chores and eliminate manual labor, enhancing productivity, and freeing up human resources for more strategic work.

8. This also allows administrators to offer highly personalized services to each person’s unique requirements while preserving uniformity of operation inside their space.

9.   

   • GenAI in human resource

   HR departments can use Generative AI to analyze candidate profiles, evaluate employees' performance, and help with onboarding by providing information on company policies and benefits.  

10.  

    • GenAI in finance

    Generative AI automates repetitive tasks, boosting productivity and efficiency, also empowering professionals to focus on more strategic work. Also, its ability to analyze large datasets and patterns opens the doors to a real-time understanding of an organization’s financial health and predicting risk on time. It helps businesses guard against anomalies, compliance issues, and fraud, strengthening finance and accounting operations. 

11.  

    • GenAI in predictive maintenance 

12. To find trends in device data, predict potential problems, and schedule maintenance in advance, Generative AI can analyze device data, which lowers costs and downtime.

"We are living in a time when technology is peaking in an unprecedented way. Each step will take us to a new reality from which we can’t step back. Its transformative powers are so intensive that they are changing people, lives, and businesses (across industries) so fast that we need to take cautious and controlled steps into them. As Generative AI is still forming, we know there are risks and challenges that can only be dealt with by experts who work with empathy, care, intelligence, and a breakthrough mindset. Nagarro drives this change for partners, helping them be meaningful and focused as they broach this irrepressible wind of change."

 

Anurag Sahay

Generative AI examples

Generative AI's capabilities include: facilitating consumer relationships, producing imaginative content for marketing and sales, and writing computer code based on natural-language cues. Businesses are using it in their own right— optimizing their functions, innovating faster, improving productivity, and reducing costs.

Here is what companies are doing with Generative AI: 

• Omnicom Group to debut tool using Generative AI for advertising employees. The tool, which uses Microsoft technology, can help build media plans and target ad audiences, among other tasks.
  
  
• Google Cloud launches anti-money-laundering tool for banks, betting on the power of AI. The company is looking to set itself apart from a crowded field of surveillance platforms by reducing the amount of human input in the process of screening for money-laundering risks. 
  
  
• GlaxoSmithKline (GSK) partnered with Exscientia to use Generative AI to identify potential drug candidates. By analyzing vast amounts of historical data, the AI system predicted which molecules would most likely be effective, reducing the time and cost associated with drug discovery. 
  
  
• The Associated Press (AP) has been using AI technology from Automated Insights to generate news articles since 2014. The AI system, called Wordsmith, can analyze complex data sets and produce coherent, human-readable reports in a fraction of the time it would take a human journalist. 

The consulting firm Accenture announced that it would invest $3 billion in AI over the next three years. 

Build your strategic edge

The transforming digital landscape is a force that is reshaping businesses and the global workforce rapidly. This is expected to accelerate, presenting a multifaceted impact on economies, societies, and individuals. 

“Generative A.I. can create “superpowers” for high-skilled workers," said Lareina Yee, a McKinsey partner and an author of the report. “The most profound change we are going to see is the change to people, and that’s going to require far more innovation and leadership than technology,” (source: New York Times).  

Building an AI-ready workforce is a strategic focus area. Are the people working with these products ready to adopt Generative AI as a solution? Also, it isn’t a developer-only solution. It requires different stakeholders to be a part of this solution, so as a strategic approach, we must have people from various roles involved in its implementation and adoption cycle. CEOs need to focus on strategic decisions that will enable them to handle the challenges and be successful with this solution adoption.   

Generative AI transformation calls for a focus on three dimensions: strength (people), structure (operations), and strategy (the thought-out and responsible plan of action). 

Strength 

Job displacement & creation: 
As automation takes over repetitive and manual tasks, there is likely to be significant job displacement. However, it is critical to recognize that automation also creates new jobs and roles that didn't exist before. The nature of jobs will change. 

Skills gap and reskilling: 
The workforce transformation brings forth a glaring challenge: the skills gap. As new roles emerge and old ones become obsolete, there is an urgent need for reskilling and upskilling. 

Quality of work: 
This creates an opportunity for the workforce to engage in more meaningful, creative, and high-value tasks. However, this positive outcome depends on how well the transition is managed. 

Mental health and well-being: 
Uncertainty about job security and the demands of adapting to new roles can cause stress and anxiety in the workforce. It's crucial that mental health and well-being are considered integral aspects of workforce transformation strategies. 

Skill augmentation: 
It is not just about replacing human effort; it's also about augmenting human capabilities. For instance, in roles like customer service, AI can provide real-time information to representatives, significantly enhancing their ability to solve customer issues. 

Personalized learning & development:  
GenAI's ability to personalize experiences extends to employee training and development. AI-driven learning platforms can create customized training programs for individuals, ensuring each employee acquires the skills and knowledge needed to excel in an AI-augmented workplace. 

Structure

Productivity & efficiency:
Automated systems will perform tasks faster and more accurately than human counterparts. This will enable businesses to achieve higher output levels and streamline previously labor-intensive processes. Prepare for this disruption. 

Organizational structures: 
The acceleration of workforce transformation is also likely to affect organizational structures. Hierarchies may flatten, and we might see a rise in more flexible and dynamic team structures. Organizations will need to be agile and adaptable to keep pace with rapid changes. 

Cognitive control: 
With AI taking over tasks that require significant cognitive efforts, leadership will have more control over the operations. 

Enhanced creativity & innovation:  
With AI taking over mundane tasks, human workers have more time and cognitive freedom to engage in creative thinking and innovation. This is particularly important in roles that involve design, content creation, and problem-solving, where AI can be used as a tool for Generating novel ideas and solutions. 

New leadership styles: 
Managing an AI-augmented workforce requires a shift in leadership styles. Leaders will need to focus on nurturing a culture of innovation, adaptability, and lifelong learning. Moreover, emotional intelligence and the ability to lead in uncertain and rapidly evolving environments will become more important. 

Strategy

Income inequality: 
The benefits of automation may not be evenly distributed. Highly skilled workers who can work alongside automated systems may see their incomes rise, whereas low-skilled workers may face unemployment or wage stagnation. This calls for robust social policies to ensure income inequality does not exacerbate. 

Geographical redistribution: 
Automation and remote working technologies may lead to a redistribution of jobs geographically. Jobs may no longer be tied to specific locations, and this could have far-reaching impacts on local economies and real estate markets. 

Ethical and societal considerations:  
The automation of work activities by AI necessitates ethical considerations, particularly in relation to bias, privacy, and the potential dehumanization of work. AI systems must be developed and implemented with ethical guidelines to augment human workers without compromising values and societal norms. 

Generative AI is the way of the future and the present. Businesses that grasp the potential of Generative AI and tools like ChatGPT to create products that improve consumer experiences will be at the forefront of this breakthrough. However, resist the urge to move forward alone with technology like Generative AI that is developing and maturing so swiftly. Rather, seek assistance and knowledge from partners, colleagues, and outside organizations active in this field. 

Nagarro's powerhouse of Breakthrough Thinking will help you adapt faster and adopt Generative AI smoothly

Generative AI, with its pathbreaking tools, is a powerful technological paradigm. But while building technology, experience matters. At Nagarro, we started very early on, setting this expertise up in 2016. Over this time, we exposed ourselves to projects, client situations, etc. As a result, we have developed a specialization around AI, including analytics, big data, IoT, conversational AI, and data science. We are the strategic partners to our clients in AI (analytics & Generative), (enterprise data product engineering), AI competency, and ML engineering, constantly helping them create solutions for them that are desirable, feasible, and acceptable.  

We act responsibly, building solutions based on the business's journey and roadmap in mind. As a responsible partner, we help our clients identify their need between the broad adoption and strategic adoption of Generative AI and see the value of the significant amount of data they possess.  

At Nagarro, we help you identify your business's most conducive use cases and stitch together the strength, structure, and strategy to implement a solution based on well-curated proprietary data. Working in a culture of customer-first approach, we will work towards increasing the value of Generative AI models by customizing them to open new economic frontiers while data opens a new world of operational accuracy.