KEY INTELLIGENCE REPORT · 2026

DONT FEEL YOUR EXPERIENCES —
SEE | MEASURE | ACTION | RESOLVE | TRANSFORM

serviceMob is the world's first data ontology and experiential analytics platform for service and support. We sit on top of the Franken-Stack, quantify 100% of behavioral experience, and feed enterprise intelligence back to the business units causing the contact demand. Model the experience. Not the contact.

Conference Guest Vault
23rd Annual · May 19, 2026 · Cambridge, Massachusetts

MIT Sloan CIO Symposium

Human-AI Synergy: Redefining Leadership for a Transformative Future

The room where CIOs, MIT faculty, founders, and board-level technology leaders align on what enterprise AI leadership actually demands next.

Register Now View 2026 Program
Leaders already in the orbit
Liberty Mutual ServiceNow Avnet Bain & Company Mapfre U.S. Navy MetLife Mathematica Home Depot Ferrovial Sysco Liberty Mutual ServiceNow Avnet Bain & Company Mapfre U.S. Navy MetLife Mathematica Home Depot Ferrovial Sysco
Why this room matters A concentrated signal source for enterprise AI leadership, buying power, and peer-level decision quality.
23rd Annual Edition A prestige CIO stage built over two decades, not a pop-up tech event.
250+ Senior Leaders Global CIOs, CDOs, CTOs, faculty, investors, and enterprise innovators.
72% Buying Influence Decision-makers with direct weight on strategic IT purchasing and transformation bets.
64% 20+ Years Deep An unusually senior room where operators trade hard-earned judgment, not surface opinions.
Conference Gravity

The CIO room that can reset your year in one day.

This is where enterprise technology leaders pressure-test AI strategy with peers who carry real balance-sheet accountability, real board exposure, and real operating complexity.

  • The Symposium has become a boardroom-grade checkpoint for leaders deciding how human judgment and machine intelligence will coexist at scale.
  • MIT faculty, award finalists, and enterprise operators share the same stage, creating a signal density most conferences never approach.
  • VIP programming begins Monday, May 18, 2026, with private roundtables, the Innovation Showcase reception, and the CIO Leadership Award dinner.
Why Leaders Show Up

Not for inspiration theatre. For strategic clarity.

Boardroom-level credibility
A room designed for leaders who have to defend transformation decisions in front of CEOs, boards, and capital allocators.
Operating models, not slogans
The strongest sessions focus on governance, workforce redesign, AI execution, and how to move from proofs of concept to economic value.
A two-day leadership arc
VIP forums on May 18 create intimacy; May 19 expands into the full Symposium stage, award panels, and Innovation Showcase momentum.
Program Snapshot

From private debate to public signal.

May 18
VIP pre-event Roundtables, formal debate, Innovation Showcase reception, and the black-tie CIO Leadership Award dinner.
8:45 AM
Opening faculty keynote The science and leadership implications behind Human-AI Synergy.
10:30 AM
Innovation Showcase pitches Ten finalists. Sixty seconds each. A tight window into what next year’s enterprise stack may look like.
2:15 PM
From Proof of Concept to P&L The marquee panel on operationalizing AI at scale with the discipline serious enterprises actually need.
Marquee Voices

The kind of stage people travel for.

MIT faculty, CIO Leadership Award finalists, and operators from some of the most consequential enterprises in the market all shape the 2026 conversation.

MIT Faculty
Tom Davenport
AI strategy and analytics pioneer bringing academic rigor to enterprise operating decisions.
Leadership Award
Ramesh Razdan
Global CIO/CTO of Bain & Company, representing the level of executive gravity that defines the room.
Faculty + Award
George Westerman
MIT Sloan senior lecturer and co-chair of the CIO Leadership Award, with a front-row view of digital leadership excellence.
Enterprise Operator
Monica Caldas
Liberty Mutual technology leadership with real-world transformation scale, not theoretical AI optimism.
$502B Lost annually from unmodeled service data
$75M+ Delivered cost savings to clients to date
R² 0.981 AMPRx correlation to CSAT & NPS
(AHT = 0.0699 / ~7%)
40–60% Of service contacts are repeat or avoidable across industries
§ The Problem

Every enterprise runs on a Franken-Stack of systems that don't talk.

Ticketing, CRM, CCaaS, WFM, BI, AI support agents — each one an island with its own data ontology. No one is modeling the full experience. That's why contact demand never changes.

CCaaS
Talkdesk · Genesys · Five9 · NICE CXone · Amazon Connect
CRM
Salesforce · ServiceNow · Dynamics 365 · SAP
Sentiment / NPS
Medallia · Qualtrics · Pendo
WFM / QA
Assembled · Calabrio · Verint · Observe.AI
AI Support
Fin · Decagon · Forethought · Sierra
BI / Viz
Tableau · Looker · Domo · Sisense
None of these systems model the experience or prevent contact demand. Case data has no connectivity to CRM, which has no connectivity to WFM, which has no connectivity to the business units that created the contact demand in the first place. The data exists. No one is reading it.
§ The Architecture

We don't replace your stack. We sit on top of it.

serviceMob ingests the dark data across every service system — including your AI solutions — engineers and synthesizes it into a single ontology, and pushes enterprise intelligence back to the business units causing contact demand.

CCaaS
CRM
Ticketing
WFM / QA
Sentiment
AI Support
BI / Viz
↑
serviceMob
Data Ontology + Experiential Analytics Platform
↑
Product
Billing
Ops
Sales / CS
Enterprise intelligence → business units causing contact demand
§ The Stack

Three layers no one else has built.

Proprietary Multivalent Ontological Blocks feed Large Ontological Models, which in turn feed LLMs — turning fragmented service data into proactive, experiential intelligence.

01 ·

MOBs — Multivalent Ontological Blocks

Capture what happens. Interaction data plus behavioral dimensions — effort, repeat frequency, resolution steps, churn likelihood — synthesized into a holistic, actionable framework. Beyond transactional, beyond AHT.

Capture
02 ·

LOMs — Large Ontological Models

Connect the insights across every system into a unified knowledge graph. This is how service stops being a siloed function and becomes a feedback loop that drives change throughout the organization.

Connect
03 ·

LOM-fed LLMs

Contextually rich, predictive outputs that service agents, managers, and bots can use in real time. The chatbot stops being reactive — it becomes proactive. Demand gets reduced at the source, not absorbed downstream.

Act
§ The Metrics

Proprietary experiential metrics that exist nowhere else.

Not AHT. Not CSAT. These are the measurements that actually correlate with business outcome — and we compute them on 100% of behavioral data, not 5% surveys.

AMPRx
Avg Minutes Per
Resolved Experience
Full experiential effort to true resolution
CPRx
Contacts Per
Resolved Experience
How many touches to actually resolve
APRx
Agents Per
Resolved Experience
Handoff burden across the journey
DTRx
Days To
Resolved Experience
Calendar time from first contact to closure
PECs
Post Experiential
Churn Score
Churn risk scored by experience signature and contact reason
R² 0.981
AMPRx → CSAT & NPS
AHT's correlation to CSAT is R² 0.0699 — roughly 7%. Every WFM, CCaaS, and BI vendor on earth optimizes handle time — and it explains almost none of the satisfaction signal. AMPRx measures the full experience and correlates at 98%. The math is the moat.
§ The Outcomes

Cost savings, measured and delivered.

Not "up to 40%." Audited, repeatable economic impact across industries.

Travel & Hospitality
$5M
9-month engagement — cost savings identified
  • 230+ excess FTEs identified
  • Full experiential baseline established
  • Contact demand mapped to root-cause business units
Home Services Decacorn
$13M
Cost deflection + 78% contact reduction
  • 78% reduction in contact rate on target issues
  • 60 FTE elimination tied to prevention, not deflection
  • Root cause fixed upstream, not absorbed downstream
Healthcare Unicorn
$7.3M
Cost deflection + forecast precision
  • 110 FTE reduction across engagement
  • 98.3% forecast accuracy at 15-minute intervals
  • Experiential forecasting replaced traditional volume-only WFM
§ The Map

Everyone else optimizes outputs. We model inputs.

The axis nobody else occupies: experience modeling × contact-demand prevention. Every category above is measured on what it actually does, not what its marketing claims.

§ Why We're Different

Six structural differences that can't be copied with a feature release.

01 ·
Ontology-First Architecture
MOBs + LOMs are a prescriptive framework, not a dashboard. Models the customer experience as structured data — POV, Channel, Phase — so service interactions, effort, and resolution become measurable inputs, not lagging outputs.
02 ·
Proprietary Experiential Metrics
AMPRx, CPRx, APRx, DTRx, PECs. Metrics that correlate to churn and revenue — not handle time and CSAT theater. Patents pending; math validated at R² 0.981.
03 ·
Forward Deployed X (FDX)
Engineers, Strategists, Data Scientists, and Contact Center SMEs embedded end-to-end. Fees cover 100% of the job. No separate SI contract, no "advisory + tool" fragmentation. We don't just give you software — we give you the experts to ensure transformation.
04 ·
Experiential Forecasting
98.3% forecast accuracy at 15-minute intervals — versus the industry standard 85–90% at 30–60 minute windows. MAPE and R² tested. Plugs directly into WFM for real staffing cost reduction.
05 ·
100% Behavioral Coverage
Surveys capture ~5% of experience at best. serviceMob models 100% of behavioral data — every interaction, every handoff, every resolution path. The thing that's never been quantified is finally visible.
06 ·
Evidence of Delivery
ezCater 8-domain maturity assessment. AT&T 30+ contact centers, 15M+ annual contacts, $40M+ identified. ServiceTitan 2,000+ accounts, five-year longitudinal analysis. Named clients. Repeatable pattern.
§ The Landscape

What every category does — and what none of them can.

An honest read of the Franken-Stack. We're not replacing any of these. We're the layer that makes them mean something.

Category What They Do What They Can't serviceMob
CCaaS
Talkdesk · Genesys · Five9 · NICE CXone
 Route & measure call efficiency Measures efficiency, not experience Models 100% of experience
CRM
Salesforce · ServiceNow · Dynamics 365
 Manage cases and accounts Manages cases, not customer journeys Ontological journey model
Sentiment / NPS
Medallia · Qualtrics · Pendo
 Survey perception 5% perception, not 100% behavior 100% behavioral data
WFM / QA
Assembled · Calabrio · Verint · Observe.AI
 Forecast volume, schedule staff Forecasts volume, ignores repeat contacts Experiential forecasting @ 98.3%
AI Support Agents
Fin · Decagon · Forethought · Sierra
 Deflect tickets with LLMs Optimizes tickets, not customer effort Prevents contact demand at source
BI / Data Viz
Tableau · Looker · Domo · Sisense
 Visualize whatever you load in Reports outputs, not inputs Ontology-grounded inputs
§ The Mob

We are a Data Ontology company.

serviceMob is the engineered intelligence layer between service data and business outcomes. We transform service from a reactive cost center into a predictive economic lever. We measure 100% of experiences. We quantify effort. We forecast experientially. We prevent repeat demand. We deliver measurable impact.

Industries We Serve
Travel & Hospitality
Healthcare
Home Services
Financial Services
Retail / E-commerce
Technology / SaaS
Telecom
Insurance
Enterprise B2B
Affiliations
Stanford StartX
Berkeley SkyDeck PAD13
MIT ILP
MIT STEX
MuckerLab
Morgan Stanley

Model the Experience.
Not the Contact.

If this made sense, the next step is a working session — 45 minutes on your data, your Franken-Stack, your experiential gaps.

Book the MIT CIO Follow-Up Session

Keep the MIT Sloan CIO Symposium conversation moving with a focused working session on your own service operation.