Business Core Solutions

The Real AI Work Is Not Prompting — It’s Orchestrating Human + AI Systems

By Prakash Palani

Rethinking the AI Narrative IT


Much of the current AI discourse is shaped by urgency and fear:
“AI is the future—learn it now.”
“Prompt engineering is the new coding.”
“AI will replace jobs unless you adapt.”

While these messages have accelerated AI awareness, they often overlook a critical question for enterprises:

After we ‘learn AI,’ what real work must actually be done?

Beyond Building: The Integration Challenge


Foundational models from OpenAI, Microsoft, Google, AWS, and Meta are already built and widely accessible. Yet, studies show over 70% of enterprises struggle to move beyond pilot projects due to integration, governance, and process alignment challenges.

Real enterprise value lies not in building new models, but in embedding AI effectively within complex business environments.

The Decline of Prompt Engineering as a Standalone Skill


Prompt engineering briefly appeared as a high-paying career path. But by 2025, it has become automated or absorbed into broader roles.

Enterprises now seek professionals who can:
  • Define and frame business problems accurately
  • Redesign cross-functional processes for AI enablement
  • Integrate AI with human workflows and existing systems
  • Establish governance, security, and compliance structures
  • Collaborate with domain experts to validate AI outcomes

  • These are the roles that sustain real AI impact.

    The Reality Inside Enterprises


    Enterprises pursuing AI adoption consistently face structural hurdles:
  • 74% struggle to scale AI beyond pilots
  • 72% report data quality and integration issues
  • 50%+ cite governance, security, and ethical gaps

  • These are not technical limitations of AI itself — they are organizational readiness challenges.

    Emerging Roles Focused on Orchestration


    Research and field practice point to a new class of AI roles built around orchestration:
  • AI Solutions Architect – embeds AI tools into business workflows
  • Process Reimagination Lead – aligns legacy processes with AI
  • Data Readiness Architect – ensures data pipelines support AI at scale
  • Human-AI Experience Designer – builds intuitive user interfaces for AI
  • AI Governance Specialist – manages risk, ethics, and compliance
  • Domain-Led AI Validator – verifies AI accuracy in specialized areas

  • These roles are not about isolated AI skills — they are about connecting technology, people, and processes.

    What Enterprises Actually Use AI For


    The most successful enterprise AI initiatives share a pattern: they integrate AI directly into existing value chains. Common focus areas include:
  • Software development acceleration (via AI copilots)
  • Customer support automation (linked to CRM systems)
  • Knowledge management and document automation
  • Fraud detection and risk monitoring
  • Enterprise operations optimization (e.g., invoice processing, logistics)

  • Each of these depends on deep orchestration of human and machine tasks.

    The Strategic Imperative: AI Orchestration


    AI orchestration—integrating AI into coordinated, cross-functional workflows—is becoming the defining capability for enterprises seeking measurable ROI.

    Without orchestration:
  • AI agents cannot act reliably
  • Automation remains fragmented
  • Investments fail to scale

  • With orchestration, AI becomes part of the operational fabric — not an isolated experiment.

    Agentic AI: Potential and Boundaries


    Agentic AI systems can execute tasks autonomously and are often viewed as the next frontier. Yet, building standalone agents will soon be commoditized. The differentiator will be leaders who know how to operationalize and govern these agents inside complex enterprises.

    This requires domain fluency, integration skills, and rigorous oversight frameworks — not just technical curiosity.

    Building the Next Generation of AI Professionals


    Enterprises should prioritize:
  • Training beyond prompting skills, focused on orchestration
  • Cross-functional teams combining business, technical, and ethical expertise
  • Investment in robust infrastructure and data integration
  • Strong AI governance and change management practices

  • Aspiring professionals must similarly build interdisciplinary capabilities that link AI technology, business processes, and domain knowledge.

    The AI Orchestration Mindset


    The future of AI will not be defined by more powerful models or cleverer prompts.
    It will be shaped by organizations that bridge people, systems, and data to deliver strategic outcomes.

    Orchestration is not just a technical capability — it is an organizational discipline.

    How Symphony and Maestro Drive This Vision


    At Business Core Solutions, our focus is on building this discipline.

    Through our flagship platforms Symphony and Anugal — enhanced with the intelligent agentic layer Maestro — we enable enterprises to:
  • Seamlessly orchestrate processes across SAP, Salesforce, cloud, and legacy systems
  • Blend human decision-making with automated execution
  • Embed AI responsibly, with traceability and governance

  • Our internal academies also prepare underprivileged youth for these new orchestration-focused careers, building a sustainable talent pipeline.

    Closing Thought


    The future of AI work is not prompting. It is orchestrating.
    Those who can unify people, data, systems, and governance will shape how AI transforms enterprise operations — and define the future of work itself.