Artificial Intelligence or Intelligent Assistants?

AI Agents, creativity and the path to practical value

Introduction

A useful thought from AI Forum 2025, recently: perhaps what we have today isn’t Artificial Intelligence (AI) but Intelligent Assistants (IA) that support human action. The hype cycle muddies expectations and no one can forecast with certainty what happens in 2, 5, or 10 years. What we can control is our posture: calm preparation, sensible adoption and clear purpose. The near-term opportunity isn’t to replace people, but to equip them with smarter tools.

A recent lecture by Dr. Lila Chrysikou, in Athens University of Economics and Business, reinforced another crucial point: creativity is not fixed; it’s trainable. Reports like the World Economic Forum’s Future of Jobs place creative thinking among the top skills shaping the workforce. Meanwhile, AI can regenerate knowledge, and not actually generate: what Gary Marcus calls an “illusion of intelligence.” So the practical question is: do we truly need Artificial Generative Intelligence (AGI), or do we need intelligent assistants that help people work better now?

What today’s AI does well

• Pattern work at scale: classification, routing, de-duplication.
• Language-heavy tasks: drafting, summarizing, translating, rewriting.
• Data extraction and structuring: pulling fields from PDFs, scans, images, emails.
• Grounded search: natural language answers with source citations (RAG).
• Workflow assistance: notifications, triggers, approvals, task routing.
• Basic analytics: trend spotting, anomalies, simple dashboards.

Where it struggles (for now)

• Reliability without grounding: hallucinations and inconsistency.
• Generalizing complex, unseen logic; brittleness at higher complexity problems.
• Numerical precision and stepwise reasoning.
• Governance,without built-in strategy: access controls, auditability, retention.
• True comprehension and intent: AI often regenerates, not understands.

Do we need AGI or better assistants?

AGI may arrive, or not. Either way, the pragmatic path is to deploy Intelligent Assistants: systems that are grounded in your data, governed by your rules, and designed to boost human creativity and judgment. Innovation is not the goal in itself, direction and outcomes are.

Creativity as a competitive advantage in an AI world

• Treat creativity as a skill: train teams in problem framing, analogy and constraints.
• Use AI for divergence and convergence: generate options, then synthesize a plan.
• Codify domain language: glossaries and synonyms improve results and alignment.
• Ask for evidence: require citations and source views for trust.
• Cross-pollinate: pair domain experts with ops/IT to design better prompts and flows.
• Protect bandwidth: remove low-value tasks so people can think, not just click.

A practical framework to turn AI into ROI: A.G.I.L.E.

Align: define the outcome (cycle time, error rate, compliance, user experience).
Ground: anchor outputs in your documents and data; require citations.
Integrate: connect to ERP/CRM/CMS; value comes from moving data where work happens.
Limit risk: RBAC, encryption, retention, DPIAs/DPAs, human-in-the-loop.
Evaluate: instrument KPIs; run short pilots and iterate before scaling.

Decision guide: when to use generative AI vs rules

1. Use generative AI for
   • Summaries, drafts, and rewrites.
   • Semantic search and Q&A grounded in your files (with citations).
   • Suggestions: classification, tagging, matching—reviewed by humans.
2. Use deterministic/rule-based flows for
   • Compliance-critical steps (approvals, postings, sensitive actions).
   • Exact calculations and reconciliations.
   • Access control, retention, and audit trails.

Governance and safety essentials

• Role-based access and least-privilege by default.
• Encryption in transit and at rest.
• Full audit logs for search, access, and changes.
• Retention/deletion policies; identifying and removing or obscuring personally identifiable information where required.
• Source citations to enable verification and trust.
• Secure integrations with defined data flows; avoid unnecessary replication.
• Protections against prompt injection/jailbreak; content safety filters.
• Clear policies to prevent training third-party models on your data.

KPIs worth tracking when adopting smart agentic tools

• Time-to-answer and time-to-find (before vs after).
• Manual entry eliminated; error rate changes.
• Percentage of cited answers accepted without escalation.
• Reduction in ad-hoc cross-team requests.
• Compliance posture: audit findings, off-policy access events.
• User satisfaction and adoption.

Conclusion

AI today is best understood as IA, intelligent assistants that help us do meaningful work faster and more reliably. Pair that capability with human creativity, sound governance, and clear outcomes, and you get real value, regardless of when (or whether) AGI arrives.

If you want to see how intelligent assistants can unlock value from your documents with safe, grounded answers and practical automations,book a short demo with PaperTrail.