AI Consulting

AI Transformation That Actually Works

Most AI transformations fail. Not because the technology is wrong, but because the approach is.

Augment your people. Don't replace them.

By 2030, According to Gartner

The question isn't whether AI will change your workforce — it's whether your organization will be on the right side of that shift.

0%

Humans Without AI

Zero IT work will be done by humans working without AI assistance.

75%

Humans Augmented by AI

The majority of work will be done by people who are made more capable by AI — not replaced by it.

25%

AI Alone

A meaningful portion will be handled autonomously — but the human judgment layer remains dominant.

Source: Gartner © 2026 Gartner, Inc. and/or its affiliates. All rights reserved.

Why AI Transformations Fail

Organizations invest heavily in AI. Twelve months later, the pilot is abandoned, the team is frustrated, and the vendor moves on.

70%

Big-Bang Thinking

They try to change everything at once. People resist, productivity drops, and the project stalls before it delivers anything.

18mo

Institutional Knowledge Ignored

The people who know your business best get sidelined instead of amplified. You lose the context that makes your organization unique.

3x

Vendor Lock-in

Building on one AI provider's ecosystem means you're stuck when pricing changes, models shift, or something better arrives.

The Two Rings

Not all work is the same. We separate organizational activity into two rings and focus where it matters most.

Fast Ring

Commodity Work

  • Summarization, translation, formatting
  • Generic chatbots and document Q&A
  • Template generation and boilerplate
  • Standard reporting and data extraction
Not our focus
Slow Ring

Core Business Intelligence

  • Domain-specific decision support
  • Institutional knowledge preservation
  • Custom workflows built on your data
  • AI that adapts to how your people actually work
Guriqo's focus

Bottom-Up, Not Top-Down

Top-down enterprise AI requires centralized IT process changes, security reviews, and role restructuring — slow and expensive. Augur deploys through tools your team already uses.

Zero IT Friction

From IT's perspective: local scripts and text files on the employee's existing PC. No servers, no cloud infrastructure, no data processing agreements. Nothing new to approve.

Same-Day Deployment

Deploy through already-approved CLIs and IDEs — Claude Code, VS Code, Cursor, Obsidian. Employees install domain-specific skill packs and start working immediately.

Project Brain

Legacy products with firmware changes, regression suites, and customer support — Augur holds the skills, memory, and context so institutional knowledge doesn't evaporate when people rotate off.

Team Brain

Shared context for a group. Same skills, same memory, same workflows. Any team member gets AI-assisted immediately without re-building context from scratch.

The Guriqo Difference

Most Consultants Guriqo
Recommend vendor, hand off to IT Build with your team, transfer skills
Big-bang transformation Incremental augmentation
Lock into one AI provider Provider-agnostic from day one
Replace humans with automation Make humans 10x, not obsolete
Deliverable: a slide deck Deliverable: working systems your team owns
Leave when budget runs out Leave when your team can run it

About Gur

Gur Sannikov, founder of Guriqo

Gur Sannikov

Founder · AI Transformation Lead

Former semiconductor AI transformation lead. Built Augur — a personal AI infrastructure system with 200+ skills, 370+ architecture decisions, and daily use across career, health, finance, and engineering. I've seen what works inside hardware companies navigating the AI shift — and what quietly gets cancelled.

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Founded by Gur Sannikov — former semiconductor AI transformation lead.