Google Ads has always been driven by data, but in 2025, it is increasingly driven by something else: generative AI. From campaign strategy to creative execution, artificial intelligence is no longer operating behind the scenes – it is taking a front-row seat in how advertisers create, optimise, and manage campaigns.
This shift is not theoretical. Google’s integration of Gemini, its flagship large language model (LLM), and the expansion of Performance Max have fundamentally changed the advertising workflow. With 94% of digital marketers already using AI within their digital advertising, it’s vital to understand how it can be integrated into the advertising workflow.
Below we look at how you can utilise Google’s latest AI developments for your ads, and why you (or your PPC management company) shouldn’t just hand over the controls to AI completely!
From Automation to Generation: What’s New?
In previous years, automation in Google Ads primarily referred to bidding strategies, ad rotations, or dynamic ad formats. In 2025, automation has been joined by generation – meaning the platform can now actively create content on your behalf.
Key developments:
- Gemini-powered asset generation: Google Ads can now write headlines, descriptions, and even suggest images based on your product or service.
- AI-assisted campaign setup: When creating new campaigns – particularly Performance Max – advertisers are offered autogenerated structures based on website content and business goals.
Conversational experience in Ads: Using natural language prompts, you can brief Google’s AI on campaign objectives and receive a ready-to-launch setup.
What once required a copywriter, designer, and campaign strategist can now be initiated with a single typed prompt. While this speed and efficiency is impressive, it raises important questions about quality, control, and performance (more on this below!).
The evolving role of Performance Max utilising AI
Performance Max (PMax) is a goal-based Google Ads campaign type that uses artificial intelligence to automatically optimise bidding, ad placements, and creative assets across all Google channels — including Search, Display, YouTube, Discover, and Gmail — to drive the best possible performance from your campaign objectives.
Performance Max (PMax) has evolved significantly since its initial rollout. In 2025, it functions as both a campaign type and a creative partner. It leverages Google’s AI to optimise bids, placements, and now, increasingly, creative combinations.
Some notable changes include:
More transparent asset performance data: Google now provides improved visibility into which creative elements are performing.
Automatic asset suggestions: If you do not upload your own visuals or copy, Google will generate them from your website, product feed, or through AI.
Advanced audience signals: Machine learning uses user intent, behaviour, and CRM lists to predict who is likely to convert – even without cookies.
However, a word of caution with Performance Max, Google (and Google sales reps!) tend to suggest P.Max to all advertisers but it is really not suitable for running small budget campaigns (less than £120/day). This is because P.Max need A LOT of data (and thus spend!) to work efficiently.
What’s more, P.Max doesn’t give the control some advertisers need – such as understanding of which keywords, audiences or ad creatives are working – meaning those that want a more specific advertising approach won’t find it useful.
If you’re running a large-scale high-spending ad campaign targeting a wide product range with mass-market appeal, P.Max is undoubtedly worth a try – although always use the AI-generated creative assets and headlines as a first draft for your own team to edit – often they won’t be a great fit for your brand voice or will read miss that human touch!
Benefits – and limitations – of AI-generated ads
When creating or editing your ads, Google’s AI assistant will suggest headlines and descriptions to help improve ad strength, which in turn will help your conversion rate (improvements of up to 12%) according to Google’s own internal data.
The advantages of AI-generated ads are clear:
- Speed: Campaigns can go from idea to launch in minutes.
- Scale: Thousands of ad variations can be tested automatically.
- Consistency: AI ensures messaging is aligned across formats and platforms.
The disadvantages of AI-generated ads:
- Creative quality: AI copy can be bland or overly formal – meaning a lower CTR (click-through-rate).
- Lack of nuance: AI may not grasp brand tone, cultural sensitivities, or subtle messaging goals.
- Doesn’t sell your USPs: Quite simply you, your marketing team or PPC agency should know the unique selling points of your brand, which Google simply doesn’t! Without highlighting these, your ad copy may read like other advertisers i.e“Great Quality Service”, “Wide Range of Products”, “Friendly Customer Service”…… Yawn!
Smart advertisers are not replacing human input – they are utilising AI as a tool to generate ideas, but using their own discretion and marketing skills to create engaging ad copy.
The Role of Smart Bidding
Smart Bidding is a subset of Google’s automated bidding strategies that uses machine learning to optimise for conversions or conversion value in every auction – a capability known as auction-time bidding. Google’s AI evaluates dozens of contextual signals in real time, such as device type, time of day, location, browser, and historical behaviour, to determine the most appropriate bid for each impression.
Advertisers who use strategies like Target CPA, Target ROAS, or Maximise Conversion Value often see steadier performance and stronger return on ad spend. For example, one of our B2B software clients transitioned from manual CPC to a Target ROAS strategy and saw a 22% increase in lead volume with a 15% reduction in week-to-week spend volatility.
However, Smart Bidding isn’t a magic wand. It works best when campaigns have enough high-quality conversion data to train the algorithms effectively. Smaller accounts or those with limited data might see inconsistent performance during the learning phase — so it’s essential to monitor closely and avoid overreacting to early fluctuations.
Broad Match: Smarter and Riskier Than Before
Broad match keywords have evolved significantly, thanks to AI-driven improvements in intent matching. Unlike the broad match of old, which matched ads to almost anything vaguely similar, today’s version uses real-time data and context signals to assess user intent more accurately. When paired with Smart Bidding, broad match can help you reach high-intent users that tighter match types might miss.
But it’s not without risk. For instance, a UK legal services client running broad match with Target CPA saw a spike in lead volume, but a chunk of those enquiries were outside their service area or not commercially viable. By tightening their negative keyword lists and adding audience filters, they cut unqualified leads by nearly 20% and improved cost per qualified lead significantly.
If you’re testing broad match in 2025, make sure you:
- Layer in audience signals or Customer Match lists
- Use clear, measurable conversion goals
- Regularly review search terms and exclude irrelevant queries
Used strategically, broad match can be a powerful way to scale – but without clear boundaries with regular monitoring and negative keywords – it can lead to lots of wasted spend.
Tips on How to Maximise Google Ad’s AI
To make the most of AI in Google Ads without losing control of your brand narrative or budget, consider the following strategies:
- Feed it high-quality inputs
Whether it is your landing page copy, brand guidelines, or product feed, the AI relies on your materials to inform asset generation. Invest time in curating accurate, persuasive content on your site. - Use AI for first drafts—not final copy
Allow AI to generate headlines or descriptions, then refine them to ensure they align with your tone, goals, and audience. - Segment your campaigns intentionally
Even with AI, campaign structure matters. Separate acquisition from remarketing, and test different audience signals for different products or services. - Don’t ignore human creative
Bespoke videos, testimonial ads, or emotionally resonant messages still outperform generic AI creatives – especially in competitive verticals. - Monitor and iterate
AI does not eliminate the need for optimisation. Set review cycles, evaluate asset performance, and A/B test where possible.
Should advertisers be concerned?
There is a valid concern among both in-house advertisers and PPC agencies that increasing AI automation may reduce their control or creative freedom. That concern is not unfounded. However, the most successful advertisers in 2025 are those who lean into the technology strategically rather than resist it altogether.
AI is a tool -not a replacement. By understanding how it works, what it can (and cannot) do, and where human oversight is still essential, you can stay ahead of competitors who are either blindly trusting it or ignoring it entirely.
As Google’s AI continues to improve, the role of the PPC professional will evolve. Expect to spend less time on manual tasks and more time on strategy, creative direction, and performance analysis.
Ready to Work With a PPC Agency that Understands AI-Advertising?
Google Ads has changed dramatically in the last 12 months – it is not just a media-buying platform – it is becoming a creative and strategic partner powered by artificial intelligence. Whether you are running a small campaign or managing millions in ad spend, adapting to this new reality is critical.
Treat Google’s AI as a collaborator: provide it with strong inputs, guide it with strategic intent, and polish its outputs with your brand expertise.
Need help navigating the transition or optimising your campaigns? Get in touch with Search Hog—we’re experienced Google Ads specialists with highly competitive Google Ads management fees that can help you make the most of your ad spend using the best bidding strategies for your account.
Contact us today to see how we can help your business.
