Intellova
Research roundup

The state of scattered business data

The average company runs 100+ apps, over half its data goes “dark”, teams lose ~a day a week hunting for it — and most AI projects fail without AI-ready data. Here's what the research says, with sources.

Every business now runs on software — but the data those tools create rarely comes back together. The result is a quiet tax on almost every company: duplicated work, reports nobody trusts, and AI projects that stall before they start. The figures below are drawn from public research by Gartner, McKinsey, Salesforce (MuleSoft), the Reserve Bank of Australia and others — every number links to its source.

Too many tools

Modern businesses run on dozens — sometimes hundreds — of separate applications, and most of them don't talk to each other.

106

SaaS apps the average company used in 2024

BetterCloud, 2025 State of SaaSOps

~29%

of an organisation's applications are actually integrated with each other

MuleSoft (Salesforce) Connectivity Benchmark, 2025

Data that goes dark

When data is spread across siloed systems, most of it is never used — and silos become the main barrier to analytics and AI.

55%

of an organisation's data is 'dark' — untapped, often unknown (long-cited figure)

Splunk, The State of Dark Data

80%

of organisations cite data integration as their single biggest obstacle to adopting AI

MuleSoft (Salesforce) Connectivity Benchmark, 2025

Time lost to busywork

Without a single source of truth, people spend their week hunting for data and reconciling it by hand.

~1 day/week

knowledge workers spend just looking for internal information (long-cited)

McKinsey Global Institute, The Social Economy

87%

of finance teams say manual data wrangling hurts the timeliness of reporting

insightsoftware, 2024 Finance Team Trends Report

Decisions made in the dark

Fragmented, untrusted data doesn't just slow decisions — it stops them.

72%

of leaders have been stopped from making a decision by the volume of data and lack of trust in it

Oracle, The Decision Dilemma, 2023

67%

of organisations don't fully trust the data they use to make decisions

Precisely / Drexel LeBow, 2023

US$12.9M

average yearly cost of poor data quality to an organisation

Gartner

AI needs a data foundation — and Australia knows it

AI is only as good as the data underneath it. In Australia, data readiness is now a named barrier to AI — and globally, most AI projects fail without it.

~⅔

of larger Australian firms have adopted AI — but legacy integration and data readiness are top barriers

Reserve Bank of Australia Bulletin, Nov 2025

~40%

of Australian SMEs were adopting AI in late 2024 (vs ~60% of firms with 500+ staff)

Australian Government, Dept of Industry, Science & Resources, Q4 2024

60%

of AI projects will be abandoned through 2026 if they aren't supported by AI-ready data

Gartner, Feb 2025

95%

of IT leaders say integration issues impede their adoption of AI

MuleSoft (Salesforce) Connectivity Benchmark, 2025

The common thread

Scattered tools create dark data, wasted time, and decisions made without the full picture — and they're now the main thing holding back AI. Unifying your data into one source of truth is the fix. That's what Intellova does: one database on AWS, dashboards in Amazon Quick Suite, and AI on a foundation you can trust.

Start your 30-day free trial

Methodology: every figure on this page is sourced from published research by the named organisation and links to the original. Figures marked “long-cited” are the most widely-referenced in their category and may predate 2023 — we flag this rather than imply they are new.