AI That Sticks Starts With Your People
Most AI initiatives in Alberta's energy sector fail not because of the technology — but because of the change. We lead with change management so your AI investments deliver lasting operational results across oil and gas, mining, and utilities.
ADKAR ADOPTION JOURNEY
Change-led AI programme · Alberta Energy Sector
Assess
Awareness + Desire
Adopt
Knowledge + Ability
Accelerate
Reinforcement
88%
avg failure rate prevented
90d
to production pilot
Prosci
ADKAR certified
Why AI Projects Fail in Industrial Operations
The data is clear. The gap between AI investment and AI results is a change management problem, not a technology problem.
McKinsey research shows the vast majority of enterprise AI initiatives never move beyond the pilot stage. The leading cause is not poor technology — it is the absence of structured change management. When frontline operators and field teams are not brought along, adoption collapses and investment is written off.
Energy companies routinely spend six to eighteen months cycling through proof-of-concept after proof-of-concept without ever reaching production scale. The bottleneck is almost never the algorithm — it is operational readiness: misaligned workflows, undertrained personnel, and leadership that has not committed to a clear use-case roadmap.
Prosci benchmarking data consistently shows that projects executed with a structured change management approach are three times more likely to meet their objectives and deliver measurable ROI. For capital-intensive energy operations, the difference between managed and unmanaged AI adoption is not marginal — it is the entire business case.
Our Approach
A structured three-phase methodology built on the ADKAR change management framework, designed specifically for industrial operations.
Assess
Understand where you stand before you build anything.
We begin by establishing a clear, honest picture of your organization's current AI readiness across leadership alignment, data infrastructure, workforce capability, and operational workflows. Using the ADKAR framework, this phase surfaces the Awareness gaps — where teams do not yet understand why change is necessary — and the Desire barriers that will determine whether adoption takes root or fails quietly. You leave with a prioritized view of your highest-value AI opportunities and the organizational obstacles standing between you and them.
Adopt
Build the capability and confidence to execute.
With assessment findings in hand, we co-design a structured 90-day implementation roadmap that sequences quick wins, a contained pilot, and a defined path to scale. This phase addresses the ADKAR Knowledge and Ability dimensions — ensuring frontline operators, supervisors, and leadership teams have the understanding and practical skills to work effectively with new AI-enabled processes. Milestones are tied to measurable operational outcomes, not just deployment dates, so progress is visible and accountable from day one.
Accelerate
Lock in gains and build the governance to keep improving.
Initial adoption is only the beginning. The Accelerate phase focuses on Reinforcement — the most commonly neglected element of enterprise AI programs. We establish the governance structures, performance measurement cadences, and reinforcement mechanisms that prevent backsliding and enable your organization to compound its AI advantage over time. This includes stakeholder engagement plans, training sustainment, and a governance model that gives leadership the visibility to make confident decisions about where to scale next.
What You Get
Tangible, actionable outputs at every phase — not slide decks, but working documents your team can execute against.
AI Readiness Assessment Report
A structured, scored evaluation of your organization's readiness to adopt and scale AI — across the five dimensions that most reliably predict whether enterprise AI programs succeed or stall.
90-Day AI Adoption Roadmap
A phased, milestone-driven implementation plan that takes your highest-priority AI initiative from standing start to validated production pilot — with frontline buy-in built in at every stage.
Change Management & Governance Plan
A living operational document that sustains AI adoption beyond the initial rollout — providing the governance, measurement, and reinforcement infrastructure your organization needs to compound returns over time.
Proven in Energy & Industrial Operations
We don't just advise on AI adoption — we build the systems. Here's where we've delivered.
FracIQ
Full-stack AI operations platform integrating 13+ technical documents with RAG pipeline, automated reporting, and real-time task management.
Frac Anomaly Detection
Production ML system using dual-head LSTM autoencoder for detecting hydraulic fracturing anomalies with 2-5 minute advance warning capability.
Predictive Maintenance ML
CLI tool and web interface for forecasting equipment failures using sensor data classification with fleet-wide batch prediction capabilities.
Operations Performance Analysis
Workforce analytics examining 1,500 employees across 6 departments using statistical methods to identify $6.5M in cost savings.
How AI-Ready Is Your Operation?
This 5-dimension assessment evaluates your organization across the factors that most reliably predict AI adoption success. Complete all 20 questions in approximately 15 minutes and receive an instant, prioritized set of actionable recommendations tailored to your industrial context.
Ready to Make AI Stick?
Start with a 15-minute assessment to understand exactly where your organization stands — then book a session to turn those findings into a concrete plan.