01
Customer Operations
Start where repeat contact reasons are stable, triage rules can be defined, and knowledge quality determines response time.
Former McKinsey Consultant • Former Senior Strategy & Operations Manager at Turo
I help operations leaders find the workflows AI can actually automate
Every company is asking how AI will change their business. Few know where to start.
11+ years leading operational transformation initiatives across McKinsey, Turo, and high-growth startups.
Experience includes
McKinsey
Turo
RepairWise
12M
Customer cases migrated
$3M+
Operational savings
$150K
Annual AP savings
Why this is not generic consulting
I have shipped the work, not just assessed it.
What that means in practice:
- Migrated 1,900 users and 12 million customer cases across five critical integrations
- Built AP automation that created real savings instead of just a cleaner demo
- Seen where automation breaks: exceptions, stale data, weak routing logic, and missing owners
- Designed workflows and the software around them, so the recommendation matches the system
The result is fewer recommendations that sit in PowerPoint and more operational improvements that keep working after the launch.
What usually breaks first
The expensive failures are usually the ones that look routine on the surface.
AP automation collapses when exceptions live in email threads instead of a controlled workflow
Support automation disappoints when every ticket gets the same priority because triage rules are vague
Dispatch breaks when branch-level capacity data is stale and nobody owns the handoff
Reporting still depends on spreadsheet stitching because nobody trusts the source of truth
Teams buy software that leaves the manual handoff in place, so the work just moves somewhere else
Leadership knows the pain is real but cannot isolate which workflow is worth automating first
Where I look first
Not every workflow deserves automation. These are the ones that usually do.
02
Finance Operations
Best for invoice intake, approval routing, duplicate detection, payout controls, and any workflow with a clear audit trail.
03
Business Operations
Useful when work crosses teams, locations, or systems and the current process depends on manual handoffs or tribal knowledge.
04
Data & Reporting
Worth fixing when leaders cannot agree on metrics, reporting takes too long, or downstream automation needs clean data to work.
How I think about ROI
Start with repetitive labor, then layer in error reduction, avoided hires, faster cycle times, and the cost of manual handoffs.
If a workflow is high volume, rule-driven, and painful to audit by hand, it is usually a candidate. If the inputs are chaotic or the owner is undefined, it usually is not.
Request an AI Opportunity Assessment →Example ROI calculation
AP team annual cost
$400,000
Estimated manual effort reduction
25%
Annual savings opportunity
$100,000
The same logic applies to support, dispatch, billing, intake, and vendor management.
WHY NOW
AI is changing how companies operate. The advantage goes to those who focus.
AI tools are more powerful and more accessible than ever. But the companies seeing real returns are not using more AI. They are using it in the right places.
They identify a small number of high-ROI workflows, redesign them, and implement solutions that work in the real world.
Why most AI projects underperform
Too broad
Trying to automate everything results in impact on nothing.
Wrong process
Automating broken workflows only makes them faster.
Poor data & integrations
AI can’t deliver value when the underlying data is messy.
No measurement
Without clear ROI, projects lose momentum and funding.
Getting AI right isn’t about more technology. It’s about making smarter operational decisions.
Case Studies
Systems I helped ship in production, not hypothetical concepts.
Turo Support Platform Transformation
Challenge
Support operations had to scale without breaking service quality, reporting, or the five critical integrations underneath it.
Solution
Led migration of 1,900 users and 12 million customer cases while redesigning support workflows and the operating model around them.
Impact
- $3M+ operational savings
- Enterprise-scale migration completed successfully
- Improved operational scalability without a service-quality drop
Customer Support Transformation
Challenge
Support volume was growing faster than the team could absorb because repeat contacts were not being routed or deflected well.
Solution
Redesigned intake, routing, and automation around the reasons customers actually contacted the team.
Impact
- 30% reduction in customer contacts
- Reduced support workload
- Better routing and faster resolution
Accounts Payable Automation
Challenge
Invoice intake, coding, and approval routing consumed recurring finance effort and created too many places for exceptions to stall.
Solution
Designed and implemented an LLM-powered workflow integrating document extraction, approval routing, business rules, and ERP workflows.
Impact
- $150K annual labor savings
- Faster processing times
- Reduced manual effort with a clearer control path
What changes when it works
The goal is not automation for its own sake. The goal is a workflow that is cheaper, faster, and easier to trust.
Less manual labor
Automate repetitive work that keeps showing up every day
Fewer repeat contacts
Better routing and self-service where the issue is obvious
Cleaner controls
Fewer invisible exceptions and fewer manual approvals buried in inboxes
Faster cycles
Less waiting on approvals, handoffs, and report pulls
Systems that can scale
Workflows that keep working as volume increases
How the assessment works
Week 1
Discovery
- Stakeholder interviews
- Workflow review
- Process mapping
- Exception and handoff analysis
Week 2
Opportunity Analysis
- Labor cost analysis
- Automation opportunity identification
- ROI modeling
- Prioritization by impact and effort
Deliverables
- Current workflow map
- Ranked AI opportunity list
- ROI estimates
- Prioritized implementation roadmap
- Build-vs-buy recommendations
- Vendor and tooling recommendations
- Data and integration requirements
- 90-day implementation plan
Start here
AI Opportunity Assessment
Most companies know AI matters. Fewer know which workflows are worth touching first.
The AI Opportunity Assessment identifies the workflows, systems, and operational bottlenecks where AI, automation, data infrastructure, or custom software can produce the highest ROI.
You leave with a practical roadmap showing where AI can reduce cost, increase capacity, improve visibility, or eliminate manual work before you commit to a full implementation.
- Current workflow review
- AI opportunity map
- ROI estimates
- Prioritized implementation roadmap
- Build-vs-buy recommendations
- Vendor and tooling recommendations
- Data and integration requirements
- 90-day implementation plan
Fixed-Fee Assessment
Includes:
- Current workflow review
- AI opportunity map
- ROI estimates
- Prioritized roadmap
- Build-vs-buy recommendations
- Vendor & tooling recommendations
- Data & integration requirements
- 90-day implementation plan
Contact for pricing.
Fee credited toward implementation if we move forward.
Request an AI Opportunity AssessmentI'll respond within one business day.
About
Khalid Alali
Former McKinsey consultant with 11+ years leading operations, product, and AI transformation initiatives in environments where the workflow had to survive production, controls, and handoffs.
I help organizations redesign workflows, implement AI, and build custom software that keeps working after the first exception shows up.
Highlights
- Former Senior Strategy & Operations Manager, Turo
- MBA, UC Berkeley Haas
- Built platforms supporting $120M+ in annual payments
- Delivered measurable operational savings across support and finance workflows
Common questions
Why not just use ChatGPT ourselves?
The prompt is the easy part. The hard part is redesigning the workflow, connecting your systems, handling the exceptions, creating auditability, managing adoption, and measuring what changed. That is where most internal attempts stall.
Do we need to replace our existing software?
Almost never. The opportunity is usually in connecting what you already have, automating the handoffs, eliminating manual steps, and making the data flow where it needs to go without a person in the middle.
What systems do you work with?
QuickBooks Enterprise, NetSuite, Sage, HubSpot, Salesforce, Airtable, Google Workspace, Slack, and most common ticketing, CRM, and ERP systems. If you have an API or a webhook, there is usually a path.
Is this strategy or implementation?
Both, but the value is in implementation. The assessment surfaces the opportunity. The engagement builds and deploys it. Strategy without a working system is just a deck.
How quickly can we see results?
Simple workflow automation can show measurable impact in weeks. More complex systems with multiple integrations or approval workflows take longer, typically two to four months to full deployment.
Find the workflows worth automating first.
Most companies are looking in the wrong places. The highest ROI is usually in the workflows that feel normal because they have been done manually for so long, no one questions them.
Request an AI Opportunity Assessment