Part of Lusha’s ongoing measurement of B2B data decay. Every finding in one place: How fast B2B contact data decays.
All data in this report is drawn from Lusha’s live signal database. Signal counts reflect contacts with a detected company change or promotion event between January 1 and June 1, 2026. Department and seniority breakdowns use Lusha contact classifications. Geography is the contact’s location as recorded at the time of the signal. All data is aggregate; no individual names or employers are disclosed. Sources: Lusha B2B Contact Change Report Q2 2026 and Lusha Executive Mobility Report Q2 2026.
60,384 IT contacts changed companies between January and June 2026. That is the second highest total of any function we report, behind Sales at 121,238.
Volume is not the interesting part. When a sales contact leaves, a record goes stale. When an IT leader leaves, a vendor evaluation loses the person running it, and a second one starts somewhere else. Two accounts change at once, and the deal that was three weeks from signature is the one that goes quiet without anybody saying why.
This report maps what those 60,384 changes mean in practice: which IT roles we counted, why IT departures create a different kind of deal risk, what we observed but did not measure, and what to do before a window closes.
What is counted and what is observed. The move totals here are counts from Lusha’s database. The evaluation windows, the tenure trends and the emerging role patterns are context drawn from how these functions behave, not values we measured. Both are useful. They are labelled separately throughout, because a count and an impression should not sit in the same column.
The numbers at a glance
Counts cover the functions and named roles we report. Other functions exist in the database and are not broken out here, so “second” describes this set rather than every department.
Part one: why an IT change lands differently
Every departure creates a data quality problem. An IT departure creates a second one: it removes the person who was running an evaluation.
At the old account, the vendor selection the departing leader was driving loses its internal advocate. Whoever arrives will look again at the decision their predecessor was about to make, and may not share the direction or the urgency. Deals weeks from signature have gone back to the start because the champion moved.
At the new account, the arriving leader is assessing an inherited stack. Every incumbent vendor is being judged, whether or not anyone calls it an evaluation, and every vendor not in the stack has a chance to be in the conversation before a view hardens.
60,384 IT contacts changed companies in the window. Each one created both situations at once. Whether either was caught depends entirely on whether anybody was looking.
Part two: the roles we counted
The IT function is not one thing, and different titles create different commercial events when they move.
CIO: 869 moves, the broadest mandate
869 CIO company changes, an average of 8 per working day, the highest named IT role count in this dataset. A CIO carries the widest buying remit of any IT title: infrastructure, security, cloud, data and AI tooling all sit under the same signature.
Context, not measurement: the scope of the role has grown faster than many organisations can sustain leadership continuity, with AI strategy and security oversight added to a traditional IT mandate. That makes the job both more attractive externally and more demanding internally, and a share of moves are people taking a larger remit rather than leaving a failure. We count moves, not tenure, so we cannot put a number on that from this data.
CISO: 287 moves, the count that needs the closest reading
287 CISO company changes, the lowest named role count here. Part of that is structural: there are fewer CISOs than CIOs because not every organisation has one, and the role concentrates in financial services, healthcare, technology and regulated industries.
Context, not measurement: the security industry widely reports falling CISO tenure, driven by regulatory pressure, the threat landscape and burnout. Our database counts moves rather than tenure, so we cannot confirm that trend or quantify it here. What we can say is that 287 is the baseline for this window. If the reported trend is real, the count should rise, and we will publish the next reading rather than forecast it.
Chief Data Officer, Chief AI Officer, Chief Digital Officer
These are the newest senior titles in the function and the ones being created, redefined and recruited fastest as AI adoption moves through enterprise organisations.
We have not published separate counts for them in this window, and until we do, treating them as the fastest growing category is an observation rather than a finding. What is true and useful without a count: a newly appointed Chief AI Officer or Chief Data Officer is assessing tooling with no incumbent relationship to defend, which is a different conversation from a replacement sale. If you sell into AI or data infrastructure, they are worth monitoring by name.
Move counts are from the database. Review lengths are a planning frame drawn from how these evaluations run, not values we measured. The same frame appears in the Executive Mobility Report.
Part three: where IT leaders moved
IT leadership moves in this window concentrate in four markets. One caveat first: the dataset was pulled globally without a geographic filter and skews European, so these describe where moves were detected in this sample rather than the relative mobility of each market.
Presence describes this sample. We have not published per country CIO counts for this window, so these are relative descriptions rather than measured shares.
Part four: the evaluation that restarts without telling anyone
The expensive version of an IT departure is not a bounce. It is a selection process that resets while every vendor in it believes it is still running.
A vendor three weeks from a signed contract when the CIO moved has a specific problem. The new CIO did not choose to evaluate them; they inherited an evaluation already underway. The natural first move is to pause, understand what they are taking on, and form a view, which may or may not match their predecessor’s. Often nothing is formally restarted. It simply goes quiet. The vendor follows up, gets no reply, reads it as a slow quarter, and the deal is already gone.
The silent restart. IT evaluations rarely announce that they have reset. They go quiet, and silence reads like a slow process rather than a changed situation. The cheapest way to tell the difference is to check whether the champion is still in seat, before the deal goes dark rather than after it is lost.
The same dynamic runs the other way at the new account. Arriving early in someone’s tenure means arriving before a framework is set. Arriving at week seven means arriving into a shortlist.
Detection lag, and what it means for “early”
Arriving early requires knowing early, and our own measurement says that is not guaranteed for any dataset, including ours.
When we measured job change rates across three windows, the three month window returned about half the monthly rate of the twelve and twenty four month windows. Job changes do not slow down in recent months, so the difference is detection lag: a change takes time to surface in any dataset that observes employment rather than being told directly. The measurement is published here.
Two consequences. Checking continuously still beats finding out from a bounce or a notification, because it is deliberate rather than accidental. And “detected this week” is not “started this week”, so run your outreach window from the start date where you have one, and treat the detection date as a floor when you do not.
Part five: three actions for technology vendors
1. Check the IT champion on every open deal on a weekly cadence. 60,384 IT contacts changed companies in five months. On your own pipeline the number is small, which is the point: it is a short list of deals where the person who was driving it may no longer be there. Weekly is enough to catch it before the silence starts. Quarterly is not.
2. Write the new leader outreach before the signal fires. A message that names the move, connects it to something specific you solve, and asks for twenty minutes is a different email from a generic introduction. It has to exist before the signal arrives, because writing it is what costs the week.
3. Treat new AI and data leadership as a named signal, not background. A newly appointed Chief AI Officer or Chief Data Officer is assessing tooling with no incumbent relationship to defend. We have not published separate counts for those titles, so monitor them by name on your own target list rather than waiting for a category number.
What we did not measure
Tenure. Every reference to declining tenure above is industry context, labelled as such. Measuring it means tracking start and end dates per person across employers, which is a different study.
Evaluation windows. The 60 to 90 day review lengths are a planning frame, not values from the database.
Emerging role counts. Chief AI Officer, Chief Data Officer and Chief Digital Officer are not separately counted in this window. Calling them the fastest growing category would need numbers we have not published.
Undetected moves. Only detected changes are counted, and detection lags reality, so 60,384 is a floor. Role totals also reflect our coverage of each title, which varies.
Methodology and data notes
Data source: Lusha live signal database, 515M+ verified contacts, signals pulled June 1, 2026.
Signal window: January 1 to June 1, 2026, 108 working days.
Signal definitions: company change signals reflect contacts where a move to a new employer was detected during the window. Role specific counts, CIO 869 and CISO 287, reflect contacts with a confirmed company change signal and a current title matching that role as of June 1, 2026. Role totals reflect Lusha database coverage and are directional rather than exhaustive. All data is aggregate; no individual names or employers are disclosed.
Geographic note: the sample was pulled without a geographic filter and skews European, so market descriptions reflect detection in this sample rather than relative mobility.
Privacy and compliance: all data is aggregated and anonymised. No individual contact details are included or derivable from the figures presented. Current certifications are listed on the trust center.
Source reports: B2B Contact Change Report Q2 2026 · Executive Mobility Report Q2 2026
Related resources
- How fast B2B contact data decays, and what it costs — every report on this, in one place
- Sales Contact Mobility Report — the 121,238 moves in the busiest function
- Executive Mobility Report: C suite, Q2 2026 — CIO, CMO, CRO and CISO compared
- Monitor CRM contacts for promotions and company changes
- Find who owns an account after your champion leaves
