Vertical Agents: Salesforce's Quantum Leap and the Dawn of Accelerated Business Value

Salesforce's recent Unveiling of "Agentforce for Health" isn't just another product launch; it's a seismic shift signaling the rapid maturation and verticalization of agentic AI. This move, coupled with the astonishing pace of Salesforce innovation, is opening up unprecedented opportunities for businesses and service providers alike, particularly for giants like HCLTech. The implications are profound: faster value realization for customers, a dramatic redefinition of business processes, and the emergence of entirely new service models.

The Power of Vertical Agents: Beyond Generic AI

For years, AI has been touted as the future of business. However, much of its application has been broad and generalized, leaving specific industry needs largely unmet. Salesforce's Agentforce for Health changes this narrative by introducing a library of pre-built, industry-specific skills. This vertical approach is crucial for several reasons:

• Domain Expertise: Healthcare is a complex, heavily regulated field. Generic AI struggles to navigate the nuances of patient data, insurance protocols, and clinical workflows. Agentforce's specialized skills, like patient eligibility checks and clinical trial analysis, demonstrate a deep understanding of the industry's unique challenges.

• Accelerated Deployment: Pre-built skills dramatically reduce the time and resources required to implement AI solutions. Instead of building from scratch, healthcare organizations can leverage existing capabilities, accelerating time-to-value.

• Enhanced Compliance: Healthcare is subject to stringent regulations like HIPAA. By embedding compliance considerations into the agent's design, Salesforce helps organizations mitigate risks and ensure data privacy.

The statistics cited by Salesforce are staggering: 87% of healthcare staff working late due to administrative burden, and the potential for 10 hours of weekly savings through agent adoption. These numbers underscore the urgent need for solutions that alleviate the operational strain on healthcare providers.

Salesforce's Innovation Velocity: A Catalyst for Change

Salesforce's rapid innovation cycle is a key driver of this transformation. Their ability to quickly develop and deploy new features and capabilities is unmatched. This agility allows them to stay ahead of the curve and respond to evolving customer needs. The introduction of Agentforce for Health, along with partnerships with athenahealth and Availity, showcases this commitment to continuous improvement.

This rapid pace of innovation has several critical effects:

• Democratization of AI: By providing pre-built skills and a user-friendly platform, Salesforce makes agentic AI accessible to a wider range of organizations, not just those with extensive AI expertise.

• Ecosystem Expansion: Partnerships with industry leaders like athenahealth and Availity create a robust ecosystem that accelerates the adoption and impact of agentic AI.

• Customer Empowerment: Customers are empowered to tap into business value at an accelerated rate, allowing them to quickly adapt to changing market conditions and improve operational efficiency.

The Agentic World: A New Frontier for Service Providers

The rise of vertical agents and the rapid adoption of agentic AI create a wealth of opportunities for service providers like HCLTech. These companies are uniquely positioned to help organizations navigate the complexities of this new landscape and maximize the benefits of agentic AI.

Here's how HCLTech and similar companies can capitalize on this trend:

• Driving Fresh Thinking: Service providers can leverage their deep industry knowledge and AI expertise to develop innovative solutions that address specific customer needs. This could involve creating custom agent skills, integrating agents with existing systems, or developing new AI-powered applications.

• Reframing Value Streams: Agentic AI has the potential to transform traditional business processes and value streams. Service providers can help organizations identify opportunities to automate tasks, optimize workflows, and create new revenue streams.

• Innovating on New Business Models: The agentic world opens up new possibilities for service delivery. Service providers can develop new business models that leverage AI to provide proactive, personalized, and always-on services.

• Consulting and Implementation: Many organizations lack the internal expertise to implement and manage agentic AI solutions. Service providers can offer consulting and implementation services to help customers navigate the complexities of this technology.

• Training and Support: As agentic AI becomes more prevalent, there will be a growing need for training and support services. Service providers can offer training programs to help employees understand and use agentic AI tools effectively.

• Data Management and Security: Agentic AI relies on vast amounts of data. Service providers can help organizations manage and secure their data, ensuring compliance with relevant regulations.

• Customization and Integration: Each organizations needs are different. Service providers can build customization into the agents, and help integrate them into the clients pre-existing systems.

The Impact on Healthcare: A Case Study

The healthcare industry is a prime example of the transformative potential of vertical agents. By automating time-consuming tasks like eligibility checks and clinical trial analysis, Agentforce for Health can free up healthcare professionals to focus on patient care. This can lead to:

• Improved Patient Outcomes: Faster access to care, more efficient treatment, and personalized support can lead to better patient outcomes.

• Reduced Administrative Burden: Automating administrative tasks can reduce the workload on healthcare staff, leading to increased job satisfaction and reduced burnout.

• Increased Operational Efficiency: Streamlining workflows and automating tasks can reduce costs and improve operational efficiency.

• Accelerated Research and Development: Agentic AI can accelerate the pace of research and development by analyzing vast amounts of data and identifying patterns that humans might miss.

Looking Ahead: The Future of Vertical Agents

The introduction of Agentforce for Health is just the beginning. As agentic AI continues to evolve, we can expect to see the development of vertical agents for a wide range of industries, including finance, manufacturing, and retail.

Key trends to watch include:

• Increased Personalization: Agents will become increasingly personalized, providing tailored experiences and recommendations to individual users.

• Enhanced Collaboration: Agents will be able to collaborate with each other and with humans, creating intelligent ecosystems that can solve complex problems.

• Improved Natural Language Processing: Agents will become more proficient at understanding and responding to natural language, making them easier to interact with.

• Edge AI Adoption: Agents will be deployed on edge devices, enabling real-time processing and decision-making.

• Ethical AI Considerations: As AI becomes more powerful, it's crucial to address ethical considerations related to bias, privacy, and security.

Salesforce's bold move into vertical agents is a testament to the transformative power of AI. By combining domain expertise with cutting-edge technology, they are empowering organizations to achieve unprecedented levels of efficiency and innovation. For service providers like HCLTech, this represents a golden opportunity to drive fresh thinking, reframe value streams, and shape the future of business. The age of agentic AI is upon us, and the possibilities are limitless.

Labels: Agentic AI, Gen AI

The Economics of AGI: Shaping Humanity's Future

Sam Altman has an interesting take titled "Three Observations" on  Artificial  General Intelligence and I thought of penning this note. In the rapidly evolving landscape of artificial intelligence, we stand at a crucial juncture where systems approaching AGI are coming into view. Our mission to ensure AGI benefits all of humanity requires a deep understanding of both its transformative potential and the challenges it presents. By examining current trends, historical parallels, and expert perspectives,  we can better navigate this unprecedented technological transition.

The New Economics of Intelligence

Three fundamental patterns have emerged in AI development that are reshaping our understanding of technological progress. First, we've observed that AI intelligence scales logarithmically with the resources invested in training and operation. This relationship, validated by OpenAI's scaling laws research, holds true across multiple orders of magnitude, suggesting we can achieve continuous gains through strategic investment in compute, data, and infrastructure. 

Second, and perhaps most striking, is the unprecedented rate of cost reduction in AI capabilities - approximately ten times every twelve months. This dramatically outpaces Moore's Law, which transformed our world at a relatively modest pace of doubling every eighteen months. The transition from GPT-4 to GPT-4o demonstrated this acceleration, with a 150-fold reduction in token cost over just one year. As economist Erik Brynjolfsson notes, this rapid cost reduction could lead to "productivity J-curves" where initial implementation costs are quickly overcome by exponential benefits.

The third pattern reveals that the socioeconomic value generated by linear increases in AI intelligence appears to be super-exponential. Stanford's AI Index Report supports this observation, showing accelerating adoption rates across industries. This creates a powerful feedback loop, driving continued investment and advancement in AI capabilities.

AGI as Infrastructure: The Transistor Parallel

Historical perspective helps us understand AGI's potential impact. Much like the transistor - a fundamental scientific breakthrough that became ubiquitous by embedding itself into every industry - AGI may become an invisible but omnipresent force multiplier for human capability. Economic historian Joel Mokyr's research on general-purpose technologies suggests that such fundamental innovations tend to create cascading effects across multiple sectors, fundamentally reshaping how value is created and distributed.

Consider the emergence of AI agents as virtual knowledge workers. While these agents may initially perform at a junior level requiring significant supervision, their scalability is transformative. Imagine a million software engineering agents working in parallel - even if individually less capable than expert humans, their collective impact could dramatically accelerate technological progress. MIT's David Autor argues that, like previous general-purpose technologies, AI will likely complement rather than replace most human work, creating new opportunities for human-AI collaboration.

The Human Element in an AI-Powered World

Despite these radical changes, many aspects of human nature and daily life will remain constant. People will continue to form relationships, seek meaning, and explore the natural world. However, the ways we work, create value, and interact with technology will evolve significantly. Psychologist Sherry Turkle's research suggests that maintaining meaningful human connections will become even more crucial as our technological capabilities expand.

In this evolving landscape, certain human qualities may become increasingly valuable. Agency and determination in directing AI tools, adaptability in a rapidly changing environment, and social intelligence in coordinating human-AI collaboration will likely be highly prized. The ability to identify new problems and opportunities - rather than simply solving existing ones - may become a key differentiator for human contribution.

Ensuring Broad Benefits

Perhaps the most critical challenge lies in ensuring AGI's benefits are broadly distributed. Economist Daron Acemoglu emphasizes that the distributional effects of AI will depend crucially on institutional choices and policy decisions made in the coming years. Early intervention may be necessary to prevent excessive concentration of power and ensure that AGI serves as a tool for broad economic empowerment rather than increased inequality.

Several approaches merit consideration, from universal compute access programs to continued focus on driving down AI costs. New economic models may be needed to balance the interests of capital and labor in an AI-driven economy. Policy frameworks must support individual empowerment while maintaining necessary safety guardrails.

Scientific Acceleration and Societal Impact

The impact of AGI on scientific progress may surpass all other effects. With the ability to process vast amounts of information and identify novel patterns, AGI could dramatically accelerate the pace of scientific discovery. This acceleration could lead to breakthroughs in healthcare, clean energy, and other critical fields that benefit humanity as a whole.

The economic implications are equally profound. As the cost of intelligence and energy - two fundamental constraints on many economic activities - potentially decrease dramatically, we may see significant shifts in the relative value of different goods and services. Luxury goods and inherently limited resources like land may see dramatic price increases, while many information-based goods could become nearly free to produce.

Looking Forward

The technical path toward AGI, while challenging, appears relatively clear. The more complex questions involve social choice, policy, and collective decision-making about how to integrate these powerful technologies into society. This requires careful balancing of safety concerns with individual empowerment, and constant attention to distributional effects.

By 2035, we should strive for a world where every individual can access and direct AI capabilities equivalent to the collective human intelligence of 2025. This democratization of cognitive resources could unlock currently constrained human potential, leading to an unprecedented flowering of creativity and innovation. The ultimate goal remains clear: ensuring AGI becomes a powerful lever for human potential, enabling individuals to have greater impact while distributing benefits broadly across society. If we can achieve this, we may be entering an era of unprecedented human flourishing and creative achievement.

As AI researcher Stuart Russell notes, the development of AGI represents perhaps the most significant technological transition in human history. The decisions we make in the coming years about its development and deployment will have lasting implications for generations to come. By thoughtfully navigating this transition, we can work toward a future where advanced AI technology enhances rather than diminishes human agency and potential.

"SUPERAGENCY: Our AI Future" by Reid Hoffman and Greg Beato

Over the weekend, finished reading Reid Hoffmans recently published book," Superagency" co written with Greg Beato. Been a great fan of Reid Hoffman, currently in the board of Microsoft reading some of his earlier books -Blitzscaling and Masters of Scale

In an era where artificial intelligence sparks both wonder and worry, LinkedIn co-founder Reid Hoffman and writer Greg Beato offer a refreshingly nuanced perspective in their new book "Superagency: Our AI Future." Moving beyond the typical AI discourse of either techno-utopian promises or existential warnings, they present a compelling vision of how AI could enhance human capability and agency on both individual and societal levels.

The book's central thesis revolves around the concept of "superagency" - a state where widespread AI adoption creates compounding benefits throughout society. Rather than focusing on AI as a replacement for human capabilities, Hoffman and Beato envision it as an amplifier of human potential, much like how the industrial revolution transformed our relationship with physical energy.

What sets this book apart is its practical approach to AI implementation. Drawing from Hoffman's extensive experience in the tech industry, the authors advocate for an iterative development process similar to how the automotive industry evolved. They argue that competition, rather than rigid safety regulations, can more effectively guide responsible AI development while maintaining innovation momentum. This perspective, while potentially controversial, is grounded in historical precedent and practical considerations.

The authors introduce the concept of a "techno-humanist compass" as a framework for guiding AI development. This approach emphasizes that technological advancement should serve human values and enhance individual agency rather than diminish it. They envision AI as a "private commons," similar to the internet, where collective contributions benefit all users while maintaining individual privacy and autonomy.

One of the book's most intriguing arguments is how AI benefits can extend beyond direct users. The authors illustrate this through practical examples: AI-enhanced healthcare making doctors more effective, multilingual ATMs serving diverse communities, or smart energy systems optimizing resource usage for entire neighborhoods. These examples demonstrate how individual AI adoption can create ripple effects that benefit society as a whole.

The book also tackles the thorny issue of AI governance, proposing what they call "Regulation 2.0." This framework emphasizes user feedback and public participation in shaping AI development, rather than relying solely on top-down regulatory approaches. While this might seem optimistic to some readers, the authors make a compelling case for how market forces and user preferences can guide responsible AI development.

Hoffman and Beato's vision extends beyond individual enhancement to addressing global challenges. They argue that AI's potential to convert "Big Data into Big Knowledge" could usher in a new "Light Ages," where data-driven insights help address pressing issues like climate change, healthcare access, and resource depletion. This optimistic yet grounded perspective offers a refreshing alternative to both doom-laden and overly rosy AI predictions.

However, the book isn't without its blind spots. The authors' background in the tech industry occasionally shows through in their emphasis on market-driven solutions and competition as regulatory mechanisms. Some readers might question whether market forces alone can adequately address ethical concerns and ensure equitable access to AI benefits. Additionally, while the book acknowledges potential risks, it could have devoted more attention to addressing specific concerns about AI safety and ethics.

The writing style strikes a balance between accessibility and depth. Technical concepts are explained clearly without oversimplification, making the book valuable for both AI newcomers and those well-versed in the field. The authors use engaging examples and analogies to illustrate complex ideas, though occasionally the business-world perspective dominates the narrative.

A particularly valuable aspect of the book is its discussion of different stakeholder perspectives on AI development. The authors identify four key groups - "Doomers," "Gloomers," "Zoomers," and "Bloomers" - and thoughtfully analyze how these varying viewpoints shape the AI discourse. This framework helps readers understand the current debate landscape while highlighting the importance of finding common ground.

The book's emphasis on iterative deployment and continuous learning offers practical insights for anyone involved in AI development or implementation. Rather than advocating for grand master plans, the authors suggest that society can collectively explore and discover AI's future through careful experimentation and adaptation. This pragmatic approach acknowledges both AI's transformative potential and the importance of responsible development.

"Superagency" is particularly relevant for business leaders, policymakers, and technology professionals grappling with AI's implications. Its framework for understanding AI's societal impact and practical approach to implementation provides valuable guidance for decision-making. However, general readers interested in technology's future will also find the book's perspectives enlightening.

In conclusion, "Superagency" offers a valuable contribution to the AI discourse, presenting a vision that is both ambitious and grounded. While some might question its market-oriented approach to regulation and governance, the book's core message about AI's potential to enhance human agency and create compounding societal benefits is compelling. Hoffman and Beato have crafted a thoughtful roadmap for navigating AI's future, one that acknowledges both opportunities and challenges while maintaining a focus on human values and collective benefit.

For those seeking to understand how AI might shape our future beyond the typical narratives of replacement or resistance, "Superagency" offers a fresh and nuanced perspective. Its vision of AI as a tool for enhancing human capability rather than replacing it provides a constructive framework for thinking about and shaping our technological future.  As someone deeply engaged in managing teams driving digital transformation initiatives across very large enterprises, I find Hoffman and Beato's vision particularly resonant, though I'd emphasize even more strongly the massive organizational change management required for this AI revolution. The transformation needed goes far beyond technology implementation – it requires a fundamental rethinking of how enterprises operate, organize, and create value. While the authors touch on organizational adaptation, my experience suggests that the scope of change is even more profound. Organizations need to completely reimagine their value chains, restructure their processes, and reshape their cultural DNA to fully leverage AI's potential for superagency.

This is where I see a crucial role for consulting firms as transformation partners. The complexity of this shift – touching everything from process redesign to cultural transformation – demands expertise that most organizations simply don't have internally. Professional services firms bring not just technical knowledge, but crucial experience in managing large-scale organizational change, cultural integration, and process reengineering. Their cross-industry exposure and proven methodologies can help enterprises navigate this complex transformation while avoiding common pitfalls. The value chain disruption we're witnessing isn't just about automation – it's about fundamentally reimagining how businesses create and deliver value in an AI-enhanced world. This requires the kind of holistic, systematic approach that experienced consulting partners can provide, helping organizations build both the technical capabilities and the cultural readiness needed for realizing the comprehensive AI's potential for superagency

Labels: Business, Future, GenAI, Society, Superagency, Technology