Changecast

How much is AI noise costing you?

Your team monitors dozens of AI tools. Every update means scanning changelogs, forwarding Slack messages, and hoping nothing slips through. Let's put a number on it.

1
Tools
2
Team
3
Results

Which AI tools does your team use or track?

Select the companies your team actively uses, evaluates, or monitors.

0
official sources across 0 companies your team would need to monitor manually

Tell us about your team

We'll calculate time wasted and the cost of staying current.

10
1 (Just me) 50 100 250 500

Your AI information cost

Based on 0 companies, a team of 0, and 0 sources to monitor.

--
return on investment — for every $1 spent on Changecast,
you recover $0 in productivity
--
hours/year your team spends
monitoring & filtering AI updates
McKinsey: 1.8 hrs/day on information search
--
annual cost of wasted
time at your team's rate
Intel: $1B/yr lost to info overload internally
--
days to pay for itself
— then it's pure savings
Bain: analytics improves decision efficiency 25%

Annual cost: doing nothing vs. Changecast

Status quo
$0
Changecast
$0
Source monitoring eliminated
--
sources auto-watched. Your team checks zero manually.
Newsletters replaced
5-10
generic AI newsletters replaced with one role-personalized feed. 117 fewer emails/day.
Duplicate research eliminated
--
hours/week your team redundantly researches the same AI updates independently.
Decision speed
+25%
faster AI-related decisions when teams have role-specific context on demand.

Research backing these numbers

[1] McKinsey Global Institute — Knowledge workers spend 1.8 hrs/day (9.3 hrs/week) searching for information, ~20% of the workweek.
[2] IDC — Enterprises with 1,000 workers waste $2.5-3.5M/year on failed search. Recreating unfound info costs $4,501/worker/year.
[3] Basex Research — Information overload costs the U.S. economy $900 billion/year.
[4] Intel (Nathan Zeldes) — Each knowledge worker lost ~8 hrs/week to information overload, costing Intel ~$1B/year.
[5] Economist Impact / Dropbox — Workers lose 553 hrs/year to distraction ($468B/yr in the US). Managers: 683 hrs.
[6] Bain & Company — Analytics can increase decision process efficiency by up to 25%.
[7] Crayon (2024) — Companies using competitive intelligence see 25% higher win rates.
[8] Pendo (2019) — Average feature adoption is only 6.4%. 64% of software features are rarely or never used (Standish Group).

Stop paying the AI noise tax

Changecast monitors 0 sources across 22 companies so your team doesn't have to.

Start free trial →