Hey AI, welcome to the team: Emergence of algorithmic enterprise

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Hey AI, welcome to the team: Emergence of algorithmic enterprise

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Do we fully understand what it means to be an AI-enabled enterprise? If a company does give primacy to Artificial Intelligence, what does that company look like? What does it take to be such an enterprise? How does it behave? What does its growth path look like and where is it headed? Who will it take along for the ride, and crucially, who will it leave behind? We unpack it for you here.

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What’s inside

  1. Transitioning to an AI-enabled businesses
  2. What if we humans stopped designing processes for humans to execute? Would we design processes differently if we had the limitless computing power of an algorithm to execute it?
  3. What becomes of humans in an AI enabled enterprise
  4. How comfortable are you with the Idea of a AI-Coworker
  5. The Algo-xperience

Transitioning to AI-enabled businesses

Companies today will begin their journey by becoming the AI-First Virtual Enterprise, evolving into the Autonomous Enterprise and finally into the Agent-enabled Enterprise

AI is now asserting its place as the cornerstone of the modern enterprise: an engine that brings alive a grand human vision by driving innovation, crafting strategy, and powering execution across every business function. To make this happen we are likely to see gigantic leaps in the way innovations scale up to become disruptions.

This point of view evaluates these disruptions, and distills the insights you need to embrace this oncoming change. Download Complete Research

What if we humans stopped designing processes for humans to execute? Would we design processes differently if we had the limitless computing power of an algorithm to execute it?

Today’s AI executes tasks designed for humans, better than what humans can do. What if, we start designing tasks to be executed by AI.

What becomes of humans in an AI enabled enterprise

We will see a proliferation of new roles that human beings will be required to play in an AI-Enterprise as it evolves. From AI psychologists who understand AI behavior, AI ethicists who guide the ethical aspects of AI behavior, to even AI trainers who train AI in much the same way as we train human apprentices today.

How comfortable are you with the idea of a AI-coworker

On a scale of 1 to 5, how comfortable are you with having an AI co-worker, or even an AI boss? As AI develops personhood, we will need to grapple with these questions as the culture of organizations evolve within the AI-enabled enterprise. This point of view explores this evolution.

Algo-xperience

If humans are hired today based on the quality of their ‘work experience’, how will AI algorithms be hired in the not too distant future? Enter the ‘Algo-xperience’ – a quantifiable measure by which you can evaluate one AI agent over another. A tangible metric of their past accomplishments, personality, biases and acquired knowledge. This point of view explores how Algo-xperience will play a role in the AI-enabled enterprise. Download Complete Research

Credits
Author@lab45: Nagendra Singh
Contributing Author: Jishnu Dasgupta

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Business model handbook for enterprise leaders

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Business model handbook for enterprise leaders

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Think your enterprise can be a leader without a well-thought business? A business model is necessary for you, as an enterprise leader, to scale your ideas, products, and services and sustain them. Here's your roadmap.

What's inside

  1. Which are the business models of the future?
  2. What is significance of business models?
  3. What are types of business models that can be referred to?
  4.  How to develop a business model?
  5. What are successful business models of last decade?

Which are the business models of the future?

Innovative technologies and novel approaches to conventional business practices are expected to drive business models in the future. Platform-based business models powered by AI, cloud computing, and blockchain are predicted to improve efficiency, streamline operations, and create new revenue streams. Immersive technologies and eco-friendly practices in the experience and creator economy enhance user engagement and provide new monetization opportunities. The machine and API economy leverage AI and automation to reduce operational costs and ensure ethical and responsible use. Platform ecosystems are also expected to support innovation and be built around data platforms used by organizations, customers, vendors, and other stakeholders. Download Complete Research

What is significance of business models?

To stay ahead in today's market, enterprises must navigate market dynamics, consumer behavior, and technological advancements. A comprehensive business model is critical to their performance, optimizing operations and generating additional revenue sources. It should identify the target audience, market segment, and describe products or services while developing strategies for marketing and sales, assessing costs, risks, and profitability. Platform-based models powered by AI, cloud computing, and blockchain will streamline operations and create new revenue streams. Innovative technologies and eco-friendly practices will enhance user engagement, providing new monetization opportunities while leveraging AI and automation to reduce costs.

What are types of business models that can be referred to?

Several business models have emerged based on specific business needs, including e-commerce, subscription, freemium, marketplace, franchise, and direct sales. Each model has unique features and advantages and may overlap with other business model features. Choosing a suitable model can help an enterprise to succeed in a competitive market. Based on research by Wipro Lab45, business models can be categorized based on various parameters such as distribution, licensing, target audience, and technology. We have classified them into six broad categories, as listed below. Most enterprises today follow one or a combination of these models based on their strategic priorities, customer preferences, market demand, and profitability. The categories mentioned are not exclusive but are the most popular. Download Complete Research

How to develop a business model?

Business model strategy refers to the design and development of the business model to create, deliver, and capture value for its customers, while achieving its overall enterprise goals and objectives. Enterprise can create a business model plan that considers all its main business model components, aligns with its aims and objectives, and changes with the market over time by following the eight phases stated below, with interactive and incremental models.

What are successful business models of last decade?

Enterprises that have thrived in the last decade have embraced novel methods to create value and gain a competitive edge. One such method is the ecosystem business model built on a digital platform. Successful ecosystem business models are founded on mutual benefit, co-creation, and collaboration. By focusing on these elements, companies can build a healthy ecosystem that delivers unique value propositions and promotes sustainable growth. Amazon and Airbnb are good examples of prosperous business ecosystems that have used these success criteria. By leveraging technology and data, successful firms have improved efficiency, created new revenue sources, and maintained a competitive edge... Download Complete Research

Credits
Author@lab45: Hussain S Nayak, Poonam Pawar

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The AI paradigm

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The AI paradigm

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Ready to navigate the AI revolution? Lab45's special report demystifies the science behind generative AI and its real-world applications. Whether you're a business leader, government official, or curious citizen, this comprehensive guide offers actionable insights for everyone. From VC investments fueling AI's growth to ethical considerations, we've got you covered. Prepare to shape a future where AI doesn't just serve us, but also serves the greater good.

What's inside

  1. Breakthroughs leading to GenAI
  2. Building blocks of GenAI
  3. How is the industry organizing itself to deliver value around GenAI?
  4. How can enterprises harness the power of GenAI?
  5. The new AI economy: New careers, new lifestyles
  6. GenAI— safety, legal, and ethical implications
  7. How can we build a better world with AI?

Breakthroughs leading to GenAI

Advanced AI models like GPT-4 are game-changers, acing academic exams but also revealing logical inconsistencies. The evolution from foundational AI models to GenAI marks a significant shift. Instead of just retrieving information, these new models compose tailored outputs like text, audio, or video. This shift has far-reaching implications, affecting enterprises, governments, and consumers alike, and changing the way we interact with technology.

Building blocks of GenAI

Building Generative AI in an organization is akin to assembling lego blocks, each serving a specific function in the overall architecture. Two critical factors, data quality and model training techniques, form the bedrock of machine intelligence. Without robust datasets and effective training, the AI's performance will be compromised. The technology stack of GenAI is layered, allowing for specialized contributions from various entities—be it startups or established companies. This modular approach enables organizations to either build their own comprehensive AI systems or collaborate with others who offer specific expertise in certain layers. Download Special Report

How is the industry organizing itself to deliver value around GenAI?

The GenAI landscape is booming, fueled by a surge in investments and an influx of new players. At the core of this excitement are foundation models like GPT-4, which are increasingly being fine-tuned for specialized industry applications. Data stands as the linchpin in this race, urging enterprises to focus on developing valuable, unbiased datasets. The impact of GenAI is already palpable across various application segments, including chatbots and search functionalities, with image and text generation emerging as new consumer app categories.

How can enterprises harness the power of GenAI?

Navigating today's competitive business landscape requires enterprises to have a well-defined AI strategy. Initially, the focus should be on leveraging Generative AI for productivity gains. As they mature, enterprises can shift towards revenue gains by developing products and services using fine-tuned or foundational models. Ultimately, the goal is to achieve innovation gains. Despite the advancements in AI, the human element remains crucial, especially in product development where GenAI aids in ideation but humans execute the final design. Additionally, GenAI is set to revolutionize marketing by enabling hyper-targeted, personalized content, tailored to individual consumer preferences. Download Special Report

The new AI economy: New careers, new lifestyles

GenAI is poised to become a catalyst for unprecedented innovation and creativity, lowering the barriers to creative expression that have traditionally required specialized skills. This technology allows anyone to generate content from a simple prompt, democratizing creativity and potentially reducing the cost of creation to near zero. However, the rise of GenAI also brings challenges and questions about the future of various professions, from legal and medical to graphic design and call centers. As GenAI becomes more integral to our lives, there's an increasing need for skilled AI trainers who can ensure the ethical and fair use of these models. These trainers will focus on eliminating biases, ensuring privacy, and maintaining regulatory compliance. Download Special Report

GenAI— safety, legal, and ethical implications

As enterprises forge ahead in the development of GenAI products and services, the need for a balanced approach that incorporates AI safety is paramount. GenAI holds the potential for both transformative benefits and significant risks, making ethical design a non-negotiable aspect of its development. Regulatory landscapes are further complicated by differing governmental priorities and concerns, leading to fragmented and often challenging-to-enforce laws. For responsible and effective regulation of GenAI, a collaborative approach between enterprises and governments is essential. Both parties must work in tandem to navigate the complex risks while enabling the technology to enhance lives, whether people directly engage with AI or not. This dual responsibility underscores the critical role of ethical considerations and safety in the fast-paced evolution of GenAI.

How can we build a better world with AI?

As we stand on the cusp of a transformative era powered by AI, Lab45 presents a compelling vision for a future where technology serves the greater good. From revolutionizing medicine and combating climate change to democratizing education and beyond, the potential for positive impact is boundless. However, this optimism comes with a note of caution. The rapid popularization of GenAI in 2023 marks a critical juncture, requiring responsible stewardship from businesses, governments, and organizations alike. The societal disruptions and ethical dilemmas posed by AI, particularly its uneven impact across socio-economic classes, necessitate careful management. As AI continues to evolve, it offers us an unprecedented tool for innovation and progress. The challenge lies in harnessing this power responsibly, ensuring that the benefits of AI are universally accessible and contribute to a better world for all. Download Special Report

Credits
Author@lab45: Nagendra Singh, Tommy Mehl, Siddhant Raizada, Arvind Ravishunkar
Contributing Authors @lab45: Arindam Chatterjee, Noha El-Zehiry, Robert Walker Cohen

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