Performance and choice of LLMs
Nick Brady, Microsoft
Watch Now23:47 Minutes The average reading duration of this insightful report.
Platform ecosystems are defined as open or closed networks where an orchestrator mediates relationships between a diverse set of complementary stakeholders. Orchestrators receive benefit from both accrued value in the platform ecosystem and in barriers to entry that ecosystems create for potential competitors. Platform ecosystems are also defined by a collaborative strategy that aims to create value for all stakeholders, including customers, partners, suppliers, and competitors.
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Ecosystem business models offer diverse benefits, as described in part one. A brief summary can be found below:
For enterprises seeking to adopt an ecosystem model, the key factors of success are listed below:
The following are the identified eight steps to develop an ecosystem business model:
The key trends in ecosystems business models being adopted by enterprises at present are as follows:
Credits
Author@lab45: Poonam Pawar
Contributing Author: Hussain S Nayak
40:28 Minutes The average duration of a captivating reports.
In today's fast-paced business landscape, staying ahead requires more than just keeping up with the latest trends—it demands innovation. This is particularly true in the realm of BPS, where efficiency, accuracy, and adaptability reign supreme. In our latest special report, we delve into the transformative power of GenAI and its profound implications for the future of BPS.
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In today's fast-paced business landscape, staying ahead requires more than just keeping up with the latest trends—it demands innovation. This is particularly true in the realm of Business Process Services (BPS), where efficiency, accuracy, and adaptability reign supreme. In our latest special report, "Business Process Services in the Era of Generative Artificial Intelligence," we delve into the transformative power of Generative Artificial Intelligence (GenAI) and its profound implications for the future of BPS.
We analyze the current state of BPS, highlighting its strengths and limitations. Traditional approaches have undoubtedly improved operational efficiency, but they often fall short in handling complex tasks that require nuanced decision-making and adaptability.
Enter Generative AI—a game-changer in the world of BPS. We explore how GenAI offers innovative solutions to longstanding challenges, from streamlining repetitive tasks to enhancing decision-making processes. By harnessing the power of machine learning and natural language processing, GenAI empowers organizations to automate workflows, optimize resource allocation, and drive unprecedented levels of efficiency.
Navigate hurdles of GenAI adoption with strategies for data governance, technical integration, and fostering a culture of AI acceptance. Our paper equips readers to overcome obstacles, ensuring successful implementation and maximizing the transformative potential of AI in BPS.
We delve into how GenAI is reshaping BPS as we know it. From revolutionizing customer service with chatbots to automating document processing tasks, the potential applications are limitless. By augmenting human capabilities with AI-driven insights, organizations can elevate their BPS capabilities to new heights, unlocking untapped value and gaining a competitive edge in the process.
But how do we quantify the financial impact of GenAI adoption? We explore this question in detail, outlining key metrics and methodologies for assessing ROI. Whether it is through cost savings, revenue generation, or enhanced customer satisfaction, the benefits of GenAI are tangible and far-reaching.
Looking ahead, we paint a compelling picture of the future of BPS with GenAI at its core. As organizations embrace AI-driven automation and innovation, we envision a landscape where BPS becomes synonymous with efficiency, agility, and strategic value creation. By leveraging GenAI to its fullest potential, businesses can future-proof their operations and thrive in an era of unprecedented digital transformation.
" Business Process Services in the Era of Generative Artificial Intelligence " offers a comprehensive exploration of the transformative potential of GenAI in the realm of Business Process Services. From addressing current challenges to envisioning future opportunities, this paper serves as a roadmap for organizations looking to harness the power of AI to drive meaningful change and unlock new possibilities. Join us on this journey as we redefine the future of BPS together.
Credits
Author@lab45: Ankit Pandey
42:08 Minutes The average duration of a captivating reports.
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.
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
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.
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.
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.
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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