Sumit Bansal⭐️ recently shared something that caught my attention: "I acquired 100+ e-commerce brands at AdYogi agency, and one of the fastest ways to win a prospect was a deep Google Ads audit." He described the old routine in a way every performance marketer recognizes: "Download massive reports. Build pivot tables. Slice by keywords, search terms, campaigns, ad groups." Then the twist: he asked Drew AI a quick one-line question and got an instant punchlist, including "14 high-intent keywords," "search term leaks," and "3 structural gaps in our PMax vs. Search split."

That contrast is worth sitting with, because it captures what is changing in paid search right now. The value of a great audit has not gone down. If anything, it matters more as accounts get more automated and competition gets tighter. What is changing is the time it takes to get from "I think something is off" to "here are the exact fixes to test this week."

Below, I want to expand on Sumit Bansal⭐️'s point as a practical guide for agencies and growth teams: what a "deep audit" used to signal, what an AI-assisted audit can unlock, and how to use the outputs responsibly so you actually improve performance instead of just producing faster noise.

Why Google Ads audits used to win prospects

A strong Google Ads audit has always been a sales weapon because it compresses trust-building. When you walk a prospect through waste, missed demand, and clear next steps, you are demonstrating three things at once:

You understand how Google Ads really spends money (not just how it is set up).
You know where profit leaks hide (not just where clicks come from).
You can prioritize actions (not just list observations).

Sumit Bansal⭐️ summarized the classic workflow: exporting reports, building pivots, slicing by keyword and search term. That work was time-consuming, but it surfaced real issues like:

Search term bloat: broad match and PMax queries drifting into low-buy-intent territory
Budget misallocation: high ROAS campaigns capped while weak ones keep spending
Structure problems: messy campaign segmentation that makes bidding and reporting unreliable
Creative fatigue: ads failing to reflect the current offer, margin, or seasonality

In many audits, the biggest breakthrough is not a clever trick. It is simply seeing the account clearly enough to make the next 5 decisions with confidence.

What AI changes, based on Sumit Bansal⭐️'s example

The core promise in Sumit Bansal⭐️'s post is not "AI can do marketing." It is narrower and more useful:

It can read the account faster than a human can.
It can point to likely issues immediately.
It can produce a clean punchlist without dashboards.

That matters because the bottleneck in most teams is not knowing that audits are valuable. The bottleneck is time and attention. When audits take days, they happen quarterly at best. When you can do an initial diagnostic in minutes, you can do them weekly, and that shifts performance.

In the example, Drew AI returned three categories of insights that map neatly to how experienced operators think:

1) High-intent keyword opportunities

"14 high-intent keywords highlighted" implies the tool is spotting terms that match purchase intent, likely with good conversion rate potential, but that are under-bid, under-budget, or absent.

In practice, this can translate into:

Adding exact match for proven converting queries
Splitting brand vs non-brand to protect budgets
Creating dedicated campaigns for best-sellers or highest-margin categories
Aligning ad copy and landing pages around those terms

2) Search term leaks

"Search term leaks identified instantly" is the polite way of saying "you are paying for traffic you do not want." This is common with broad match, PMax, and accounts with limited negative keyword hygiene.

A good leak fix list typically includes:

Obvious irrelevance negatives (free, jobs, DIY, used, meaning-based mismatches)
Competitor research terms that never convert
Informational-only queries that belong in SEO or upper funnel content
Location or audience mismatches (if you only ship to certain regions)

3) Structural gaps between PMax and Search

"3 structural gaps in our PMax vs. Search split" is especially timely because many teams treat PMax as a black box. The reality is PMax and Search can either complement each other or cannibalize each other.

Common structural gaps include:

No clear intent separation (PMax takes demand that Search could capture more transparently)
Weak feed and asset coverage (PMax underperforms because inputs are poor)
Missing exclusions or brand controls (brand queries inflate performance and hide true incremental value)

A practical AI-assisted audit workflow you can run this week

If you are an agency or an in-house growth team spending serious budget, the goal is not to replace your operator instincts. It is to use AI to get to the right questions faster.

Here is a simple workflow that mirrors what Sumit Bansal⭐️ described, without requiring a full reporting project:

Step 1: Ask one focused question

Instead of "audit my account," start with something like:

"Where are we wasting spend in the last 30 days, and what negatives should we add?"
"Which campaigns are budget-capped with strong conversion performance?"
"Where is PMax overlapping with Search, and what should we change first?"

The tighter the prompt, the more actionable the output.

Step 2: Convert the output into a punchlist with owners

AI outputs are only useful if they become tasks. Turn the findings into a list with:

Action (what changes)
Scope (which campaign, ad group, asset group)
Risk level (low, medium, high)
Owner (who implements)
Measurement plan (what metric should move and by when)

The difference between "insight" and "impact" is a task list plus a measurement plan.

Step 3: Validate with quick spot checks

Speed is great, but do not skip verification. Do fast checks like:

Pull the top search terms for the flagged campaigns and confirm irrelevance
Compare impression share and lost IS (budget) on the suggested high-intent areas
Review PMax insights (search categories, placements where possible, feed diagnostics)

You are not trying to rebuild the pivot-table era. You are sanity-checking the AI so you can act confidently.

Step 4: Run 1 to 3 controlled tests, not 20 changes

AI can surface many opportunities. Your job is to prioritize:

Start with waste reduction (negatives, exclusions, budget reallocations)
Then tackle structure (segmentation, brand controls, PMax inputs)
Then expand (new keyword sets, new landing pages, new creative)

Make changes in batches small enough that attribution is not impossible.

Where teams can get burned (and how to avoid it)

If AI makes auditing easy, the new risk is doing too much too fast.

A few guardrails:

Do not blindly add hundreds of negatives without reviewing edge cases.
Be careful with PMax changes that reduce volume but also reduce incremental value, measure incrementality where you can.
Keep a changelog, otherwise you will not know what caused improvements or drops.
Remember seasonality and promos, a "leak" last month might be a winner during a sale.

What I think Sumit Bansal⭐️ is really pointing to

The line that landed for me was: "No dashboards. Just a clean punchlist you can act on today." That is the shift.

In a world where everyone can build dashboards, the differentiator is not reporting polish. It is decision velocity, paired with good judgment. If an AI tool can compress the diagnostic phase from days to minutes, agencies can:

Deliver value earlier in the sales process
Run more frequent account health checks
Spend more time on creative strategy, landing page quality, and experimentation

And if you are a growth team, you can stop waiting for quarterly audits and start treating performance like an ongoing operating cadence.

Sumit Bansal⭐️ also mentioned a simple offer for teams spending $10k+/month: comment "AI Agency" to pilot for free. Whether you use Drew AI specifically or another workflow, the bigger takeaway is worth testing: can you turn audits into a continuous habit, not an occasional project?

This blog post expands on a viral LinkedIn post by Sumit Bansal⭐️. View the original LinkedIn post →