Where nine leaders from across the MBP Group platform actually stand — and what the data says about what comes next.
9Responses
6Companies Represented
2.4Vision Clarity / 10
100%Want Training
Chapter 01
Where the Platform Stands
AI Maturity Stage
A Platform in Mid-Transition
Leaders across the platform don't see themselves in the same place. The majority have crossed into early experimentation — but the starting line and the pace differ significantly across business units.
3
Awareness
AI interest is growing, but real adoption is still minimal. Still in "watch and learn" mode — not yet running pilots at scale.
5
Activation
Early pilots are underway to test value and learn fast. The majority of the platform is here — experiments running, outcomes still being proved.
1
Operational
Has seen initial success and is scaling AI at a production level. One BU is ahead of the curve — and worth studying as a model.
What the split means: MBP Group is not a laggard — it's a platform with real momentum in pockets. The Activation majority is exactly where AI programs tend to break down. Early pilots succeed; then nothing scales. The work now is converting proof-of-concept into platform capability.
Chapter 02
The Competitive View
Competitive Position
Most Leaders See Risk, Not Advantage
When asked where they believe MBP Group stands relative to its closest competitors in AI adoption, the responses reveal a platform that sees itself as vulnerable — not leading.
Position on the Competitive Spectrum9 Responses
Significantly BehindSlightly BehindAbout the SameSlightly AheadSignificantly Ahead
2Sig. Behind
2Slightly Behind
4About the Same
1Sig. Ahead
4 of 9 leaders believe MBP Group is behind its competitors in AI. Only 1 believes the platform is significantly ahead. The window for "watch and learn" is closing.
— Survey signal · competitive positioning
Chapter 03
The Vision Gap
AI Vision & Strategy Clarity
Pilots Running. Roadmap Missing.
Leaders rated the clarity of MBP Group's long-term AI vision on a scale of 0 to 10. The result is one of the most telling numbers in this entire survey.
2.4/10
Average Vision Clarity Score
All 9 respondents answered. The range ran from 0 to 6 — two leaders rated vision clarity at zero. No one scored it higher than a 6.
Individual Scores (0–10)
1
MBP Corp
2
Millwork 360
6
Summit Stairs
0
HBG Products
4
Paragon Stairs
3
MBP Supply Chain
5
Millwork 360
1
Marwin Company
0
MBP Corp
The interpretation: A platform with live pilots, active experiments, and leadership engagement is running without a shared map. That's not a failure — it's a call to action. Building the roadmap is the most leveraged thing this group can do today.
Chapter 04
The Foundation Assessment
Organizational Readiness — 7 Pillars
Culture Is the Hidden Asset. Budget Is the Ceiling.
Each leader rated how well seven organizational components support a scalable AI strategy. The pattern is clear: the people and culture are ready. The systems and resources are not.
Response-Level Heatmap — Each Row = One Respondent
Respondent
Leadership
Data Infra
IT Governance
Budget
Culture
Legacy Tech
Documentation
MBP Corp 1
NI
NI
NI
NI
Strong
Adq
NI
Millwork 360 A
Adq
NI
NI
VP
Strong
VP
NI
Summit Stairs
Adq
NI
NI
NI
Strong
Adq
Adq
HBG Products
NI
NI
NI
NI
NI
NI
NI
Paragon Stairs
Strong
Strong
Strong
NI
Strong
Strong
NI
MBP Supply Chain
Strong
NI
Adq
Adq
Strong
NI
NI
Millwork 360 B
NI
NI
NI
NI
NI
VP
VP
Marwin Company
Strong
Strong
Strong
NI
Excel
Adq
Adq
MBP Corp 2
Strong
Adq
Adq
NI
Excel
NI
NI
Key:VP = Very PoorlyNI = Needs ImprovementAdq = AdequateStrongExcellent
Platform Averages (out of 5)
Chapter 05
The Skill Landscape
Self-Reported AI Skill Level
The Majority Is Still Early.
Leaders rated their teams' overall AI skill level. The picture is honest — and typical for a platform at this stage. Most teams are between Novice and Basic. Two BUs have cracked Intermediate.
Novice
4
Teams just getting started
Basic
3
Beginning to experiment
Intermediate
2
Using AI in workflow
Advanced
0
Not yet — that's the goal
The opportunity: 44% of teams are at Novice — exactly the stage where structured training creates the fastest, most visible lift. 22% are at Intermediate and can become the internal champions and peer coaches the rest of the platform needs.
Chapter 06
The Fears in the Room
Biggest Concerns Around AI Adoption
Security Leads. Change Management Is Right Behind.
Leaders selected up to three concerns. The top cluster reveals a platform worried about both governance risk and organizational readiness — and importantly, about knowing where to even begin.
Security shows up in 7 of 9 responses — it's real and must be addressed. But Change Management at 6 of 9 and "We don't know where to start" at 5 of 9 are more instructive. Those aren't technology gaps. They're strategic and leadership gaps — and they're exactly what today is for.
— Workshop framing · concern analysis
Chapter 07
The Unanimous Signals
100% Consensus — No Exceptions
Two Things. Nine for Nine.
In a survey with nine distinct perspectives from six different companies, two questions produced complete unanimity. These aren't preferences — they're mandates.
9/9
100%
Want Training
Every single respondent selected Training as the enablement that would most accelerate adoption. This is not a request — it's a prerequisite. Hands-on, practical, role-specific training is the unlock.
9/9
100%
See Data & Analytics as the #1 AI Advantage Area
Nine leaders from six different companies, with different functions, markets, and tech stacks — all pointed to Data Analysis and Business Intelligence as the most significant AI opportunity in the next 12 months.
Other Enablement Needs (select all that apply)
Chapter 08
Where AI Wins the Business
AI Competitive Advantage Areas — Next 12 Months
Data Wins Unanimous. Three More at 7 of 9.
Beyond the unanimous Data & Analytics pick, three areas tied at 7 of 9: Customer Experience, Operational Efficiency, and Supply Chain. Together, these four form the core of MBP Group's near-term AI agenda.
Chapter 09
Already In Motion
Current AI Use Cases Across the Platform
Five Live Experiments. More Than You Realize.
When asked for an example of an AI use-case already implemented or in progress, the responses revealed a platform with more momentum than it typically gives itself credit for. These are real — not aspirational.
Millwork 360
Quote-to-Order (Q2O) Process Automation
Working with a consulting partner to bridge five siloed quoting and ordering systems. The process is 30% AI, 40% custom coding, 30% integration. A foundational platform play.
Operations
MBP Supply Chain
Trade Compliance Navigation
Using AI to navigate the rapidly shifting tariff and trade compliance landscape — an area of intense relevance given MBP's $95M+ annual material spend and exposure to import cost volatility.
Supply Chain
Paragon Stairs
Marketing Automation
Running AI-assisted marketing campaigns and content generation at a production level. The most operationally mature BU in the survey — already scaling, not just piloting.
Marketing
Summit Stairs
Recruiting & Screening
Using AI to enhance hiring — screening candidates and accelerating the selection process. A people-side use case that's often overlooked but delivers fast, measurable time savings.
HR / Talent
Marwin Company
New Customer Attainment
Applying AI to the front end of the sales funnel — targeting, identification, and outreach for new customer acquisition. Early-stage but strategically aligned with the platform's revenue growth mandate.
Sales
HBG Building Products
No Active Pilot
Identified as still in Awareness stage with no current AI implementation. Strong candidates for production scheduling and forecasting automation — both flagged as priority workflows.
Opportunity
The platform insight: Five of six companies have something running. The challenge isn't getting started — it's connecting these experiments into a coherent platform strategy, sharing what's working across BUs, and allocating resources to scale the winners.
Chapter 10
The Leadership Signal
Leadership Readiness to Redesign
The Ceiling Isn't the C-Suite.
Leaders responded to the statement: "Our leadership is ready and willing to challenge and redesign roles, processes, and decision-making models when AI offers a better way forward." The answer was remarkably clear.
Agreement with leadership readiness to redesign for AI
9 responses
2
Strongly
6
Agree
1
Neutral
Strong Agree — 2 respondents (22%)
Agree — 6 respondents (67%)
Neutral — 1 respondent (11%)
8 of 9 leaders — 89% — agree or strongly agree that leadership is ready and willing to challenge how work gets done. The constraint isn't will. It's clarity, resources, and a roadmap. Those are solvable problems.
Chapter 11
What Leaders Want to Fix
Top Workflow Priorities
The Backlog Is Already Written.
When asked which workflows they'd most like to improve with AI or automation, leaders named real bottlenecks — not abstract use cases. Across the platform, distinct themes emerge.
Workflow Priorities — Cross-Platform
Production scheduling & capacity planning
Quoting, estimating & Q2O process
Sales pipeline & lead qualification
Marketing communications & content
Reporting & business intelligence
Inventory & PO management
Customer contracts & agreements
Supply chain & material management
Forecasting & demand planning
Bid evaluation & procurement
What Would Most Accelerate Adoption
9
Training
Universal — every single respondent
5
Use-Case Playbook
A shared guide of what works and where to start
5
Approved Tools
A vetted, sanctioned toolkit — security guardrails included
5
Internal Champions
Peer-led change is faster than top-down mandates
5
Leadership Mandate
Encouragement and direction from the top
Reading the Survey
Five Signals From the Data
Signal 01
The platform has momentum — but no shared map.
Five BUs have live pilots. Eight of nine leaders say leadership is ready. Yet vision clarity sits at 2.4/10 — two leaders scored it zero. The platform is in motion without a destination. That's the first thing to fix.
Signal 02
Culture is MBP's strongest AI asset. Budget is the ceiling.
Culture scored highest of all seven foundation pillars (3.78/5). Budget scored lowest (2.00/5). The will is there. The resources need to follow — or the experiments will stall at pilot stage forever.
Signal 03
Training isn't optional. It's the unlock.
100% of respondents — no exceptions — said training would most accelerate adoption. With 44% of teams at Novice, structured, practical skills-building is not a nice-to-have. It's the foundation everything else requires.
Signal 04
Data & analytics is the consensus AI priority.
Every leader across every BU picked Data Analysis and Business Intelligence as the top AI advantage area. This alignment is rare. It should drive the platform's first coordinated AI investment — a shared BI and analytics capability.
Signal 05
The quoting bottleneck is a platform-wide opportunity.
Quoting, estimating, and Q2O processes surfaced across multiple BUs independently. Millwork 360 is already in motion. The others have the same pain. Solving this at platform scale — not just per BU — could be the highest-ROI AI play in the portfolio.
The Opening Question for Today
If MBP Group left today with one thing — what should it be?
A shared AI vision and a prioritized use case list that every BU president can stand behind. Not another pilot. Not another tool. A platform-level strategy that converts individual experiments into a collective capability.