The Gen AI Horizon: Build Software Smarter and Faster

Jan 23, 2025 | min read

Lucas Persona

The Gen AI Horizon: Build Software Smarter and Faster

Fifty-three percent of enterprises are using Gen AI right now to speed up software development. That’s for good reason. The software development lifecycle (or SDLC) already has checks in place to maintain quality assurance, regulatory compliance, and human oversight. As a result, it’s arguably the safest business process to augment with Gen AI.

But most orgs are only exploring proofs of concept that can fast-track coding – without considering the rest of the SDLC. That’s a mistake for any org that wants to achieve hyper-efficiency: a 10x productivity boost from end to end.

In this piece, we’ll explain why focusing on coding alone is such a serious problem. We’ll also share a smarter path forward: accelerating the entire SDLC with the help of an enterprise-ready Gen AI platform.

Gen AI Can – and Should – Do More Than Speed Up Coding

Gen-AI-assisted coding is so enticing that Gartner predicts 75 percent of software engineers will use AI code assistants by 2028. But if orgs focus on deploying AI for coding alone, they may inadvertently hamstring their software development process.

That’s because faster coding can quickly create bottlenecks both upstream and downstream. For instance, an AI-assisted software engineering team might code 50 percent more efficiently. But it might also force the product team to pump out requirements at a breakneck pace. And slam the QA team with dozens more features to test.

Without Gen AI to assist with heavier workloads, the rest of the SDLC could screech to a halt – or worse, rely on cutting corners to keep things flowing.
The good news is that Gen AI can support teams at every stage of software development. It’s the best way to avoid the bottlenecks above – and ultimately achieve hyper-efficiency. We’ll explain more in the next section.

To Achieve Hyper-Efficiency, Use Gen AI At Every Stage of Software Development

Gen AI can accelerate software development from end to end. Consider these six practical use cases:

Discovery and ideation: Gen AI can help generate ideas, define solutions to test, and better understand the range of user problems at hand. Instead of throwing ideas at the wall, Gen AI can function as a sort of funnel to help identify the most promising solutions.

Product design: Designers can use Gen AI to get a handle on user needs, create product visualizations, and even create videos to pitch prototypes. They can also use it to analyze user feedback – compressing months of work into weeks.

Backlog management: Manually breaking down the backlog can take as many as 16 hours every two weeks. But Gen AI can automate much of this work by defining priorities and code requirements in an easily digestible way. The result: the same work output in just 2 hours.

Understanding and maintaining code: In many enterprise environments, the codebase isn't new – some sections may be a decade old or more. Gen AI can help developers understand legacy code, generate up-to-date documentation, and identify where changes need to be made.

Testing and quality assurance: Gen AI can automatically generate both unit and integration tests to enable faster-paced testing overall.

Deployment and release management: Gen AI can assist in creating deployment scripts, release notes, and more – supporting smoother product launches and more agile release management.

When applied in tandem, each of these use cases can propel orgs toward hyper-efficient software development. The result, more often than not: faster time-to-market, higher quality products, and a more agile response to changing business demands.

An Enterprise-Ready Platform Can Deliver Quick Gen AI Wins

It’s clear that Gen-AI-powered software development can result in huge productivity gains. And the best part is that orgs don’t have to wait years and waste millions to see results.

With an enterprise-ready Gen AI platform like CI&T FLOW, orgs can use Gen AI today to achieve quick wins from end to end.

FLOW gives orgs the flexibility to use a range of Gen AI tools (whether that’s the latest GPT, Claude, or Gemini model) for practically any task. The platform empowers development teams by equipping them with AI agents that function as sparring partners of sorts. These agents can augment human capabilities – and even improve them – without taking on the essential higher-level work that humans do best.

In fact, with FLOW-powered software development, companies like Bulla and Sami Saude have been able to see…

50 percent faster pre-development work.
80 percent faster test generation.
75 percent faster user story creation.

Used right, FLOW can actively transform the way software teams work. And with tools to enable hyper-efficiency, orgs can see rapid results in everything from new product creation to app modernization projects.

Feel Gen AI’s Impact From Week One

Gen AI Can – and Should – Do More Than Speed Up Coding

To Achieve Hyper-Efficiency, Use Gen AI At Every Stage of Software Development

An Enterprise-Ready Platform Can Deliver Quick Gen AI Wins

Feel Gen AI’s Impact From Week One

If there’s one thing we want you to take away from this piece, it’s that Gen AI doesn’t have to be daunting when it comes to augmenting software development. You can start using Gen AI on Monday and feel the impact before the week is out. And by integrating Gen AI into every phase of the SDLC, you can unlock new levels of productivity and innovation.

Of course, when it comes to hyper-efficiency, software development is just one area to set your Gen AI sights. Stay tuned for two more blog posts in this series that dive into more business processes worth accelerating.

In the meantime, if you’re curious about how to get started with FLOW, don’t hesitate to reach out. We’d love to start a conversation.

The Gen AI Horizon, Part 2: Personalize the Full Customer Experience, From Sales to Support

In the last part of this blog series, we explored how Gen AI is changing the software development life cycle. (Doesn’t sound familiar? Take a few minutes to check out that piece before you forge onward.)

There’s another frontier on the Gen AI horizon, though: the customer experience. For years, customers have broadcast just how much they care about personalization. But many organizations don’t meet that expectation – and customer satisfaction suffers.

With Gen AI squarely in the picture, though, organizations now have the tools they need to personalize the full customer experience. Let’s take a look at three key use cases – and a helpful starting point for embracing “experience AI.”

1. Give Customers Personalized Experiences They’ll Actually Love

Many companies already give customers personalized experiences to handle common activities. But these tools are either too rigid or provided as traditional chatbots that have a penchant for frustrating customers.

A Gen AI personalized experience can engage with customers in a way that feels far more convincing and appreciated. The experience, either embedded in the solution or as personalized agents can adapt their messages or responses based on the specific context of each interaction, helping customers find what they need while making them feel seen and understood.

For example, consider a retail ecommerce setting. A customer using a Gen AI personalized experience could...

- Build a shopping list from scratch based on their preferences.
- Compare two products, highlighting the pros and cons of each either in a conversational style or as personalized product pages.
- Quickly digest customer reviews to better understand whether a product is right for them.

Amazon’s Rufus puts this kind of Gen AI into action as a chatbot. Rufus helps customers navigate product choices and make more informed purchasing decisions. What's more, the bot is integrated early into the shopping experience to guide customers when they're most likely to need support.

Walmart, on the other hand, is embedding personalized Gen AI experiences directly on Walmart.com to generate a unique homepage for every shopper.

The bottom line: by providing more natural, contextual, and personalized experiences with Gen AI can impress users and improve the customer experience.

2. Equip Customer Support Agents with Instant Customer Knowledge

Even with incredibly capable personalized experiences, there’s a high chance that customers will want to talk to a human for support. In these interactions, it’s crucial for teams to have the tools they need to provide tailored guidance.

Here, Gen AI can act as a knowledge explorer, allowing support agents to find specific answers to customer queries without defaulting to generic responses.

For instance, imagine an agent receiving a question about a product feature. Instead of manually searching through the company’s internal knowledge base, they could use a Gen AI tool trained on that knowledge to find an answer instantly. This kind of personalized support helps the agent resolve the issue faster, resulting in a more positive experience for the customer.

In experiments with CI&T clients, knowledge explorers powered by Gen AI have relied on curated private knowledge bases to...

- Generate contextually accurate answers that reference specific internal sources.
- Align answers to each user’s level of access, ensuring that they only receive the information they’re authorized to see.
- Offer step-by-step guidance to help resolve customer concerns.

The results? Faster issue resolution, reduced response times, and happier customers.

3. Make It Easy to Uncover New Sales Opportunities

When it comes to personalization, sales teams also stand to benefit from Gen AI. Imagine having an AI sales assistant that can score leads, identify promising prospects, and generate personalized sales scripts – all in real-time. That’s exactly what Gen AI can deliver.

But there’s more. Gen AI can also support sales reps in finding cross-sell and upsell opportunities. Much like the knowledge explorer used in customer support, an AI assistant can quickly access the information a sales rep needs to recommend complementary products or services.

For instance, an AI assistant could help a sales rep at a financial services firm selling to a recent college graduate by suggesting a beginner-friendly investment account or a low-fee credit card designed to help them build credit. This means that sales reps can make smarter, data-driven recommendations on the spot – and boost customer loyalty in the process.

To Embrace Experience AI, Start Small

Many organizations see the potential of Gen AI and are eager to jump in by building custom models that do it all. However, the reality is that developing custom Gen AI models is resource-intensive and requires vast amounts of data, computational power, and time.

Fortunately, most organizations don’t need to reinvent the wheel to see results. Existing Gen AI models can be used to deliver real value quickly – and often at a fraction of the cost.
Here’s how to get started:

- Identify serious pain points: Do customers complain about a scattershot support experience? Do your sales reps struggle to make personalized recommendations? These are often the highest-impact areas for Gen AI. By identifying them at the start of your project, you can pinpoint use cases likely to deliver the greatest value.
- Establish curation intelligence: All the use cases we’ve discussed involve training models on internal knowledge, prompts, and content. This way, Gen AI can present the right information to the right user at the right time.
- Test third-party models: Existing third-party models like ChatGPT, Gemini, or Claude can be a great way to start exploring the potential of Gen AI. Platforms like CI&T FLOW make it easy to test these models to see which one delivers the best results for your use case.

By starting small and focusing on targeted, impactful projects, organizations can unlock quick wins, build momentum, and demonstrate the value of Gen AI to stakeholders.

Personalization Doesn’t Have to Come at the Cost of Scale

Historically, personalization has always been seen as a tradeoff against scale. Personalizing a customer’s journey takes time, which means companies often have to choose between creating a personalized experience and reaching as many customers as possible.

Now, organizations can use Gen AI to personalize the customer experience at scale – without sacrificing efficiency. And the use cases we’ve discussed here are just the beginning. In our final blog of this series, we’ll explore how Gen AI can transform marketing processes to speak to customers’ individual needs – all without sacrificing the efficiency teams need to stay afloat.

More on that soon. In the meantime, if you’re still curious about how Gen AI can transform the customer experience at your organization, we’d love to hear from you.

The Gen AI Horizon, Part 3: Scale Your Marketing Organization

In the first two installments of this blog series, we explored Gen AI’s impact on software development, customer support, and sales. But 34 percent of organizations using Gen AI say marketing is actually where they use Gen AI most. And we’re seeing the most value when it comes to content, design, and campaign production.

That makes sense in context. Historically, orgs have had to balance content personalization and campaign production at scale. But deep personalization takes time – time that many marketers don’t have. So overstretched teams chose the latter, sacrificing tailored content in an effort to cast as wide a net as possible with their content.

With Gen AI, though, orgs don’t have to make a choice. They can personalize at scale – and reap the benefits of both strategies. In our final installment of this blog series: three use cases that showcase how.

1. Deepen Your Audience Analysis and Campaign Strategy

Marketers sit on a goldmine of audience data – but many struggle to use that data to adequately tailor their messaging. Gen AI can help by analyzing datasets to surface patterns and trends that inform more targeted campaigns.

For example, a skincare brand could use Gen AI to analyze customer reviews and identify recurring concerns about dry skin. These insights could inspire product-specific campaigns addressing this exact pain point. 

If that brand wants to break into a new market, it could deploy Gen AI to determine audience pain points by analyzing local search data, social media discussions, etc. – making it easier to reveal unmet consumer needs and adjust their campaign messaging accordingly. 

The brand could also use Gen AI to assess content preferences on an ongoing basis, tracking what resonates most with each audience to proactively adapt and refine their campaign strategy.

The bottom line? Gen AI empowers marketers to unlock the audience insights they need to support deep personalization.

2. Draft Hyper-Personalized Messages (Written and Visual)

With rich audience knowledge in tow, marketers can use Gen AI to craft hyper-personalized messages that resonate across formats and channels. Your team can use it this technology to can generate:

Blog posts that address specific industry challenges.
White papers that appeal to decision makers.
Social media copy that excites and delights customers.
Drip email campaigns that address concrete pain points.
Display ads tailored to each customer’s unique needs.

One real-world example? Michaels uses Gen AI to support its email campaigns. After embracing this technology, the company went from personalizing just 20 percent of their campaigns to personalizing 95 percent—and saw a 25 percent boost in clickthrough rates. 

Text-forward Gen AI marketing use cases are exciting enough on their own. But there's another emerging frontier for hyper-personalization: AI-generated video.

In fact, one company – Carvana – has already used Gen AI for this purpose. It created over 1.3 million unique videos to help customers celebrate their car-buying journey.

First, the Carvana team identified key data points such as customer name, purchase date, location, and cultural context. Then, it used Gen AI to create video snapshots for every customer with those details woven in. Consider Holly, for instance – a Minnesota resident who bought a red Corvette on September 29, 2019. She might receive a video referencing:

Holidays on or around the day of purchase (in this case, National Coffee Day).
Destinations she can travel to (e.g., Lake Superior).
Trendy pop culture topics at the time (like that flop of a Game of Thrones finale).

Gen AI didn't just make this kind of personalization possible – it paved the way for unforeseen efficiency. Carvana was able to produce over 300,000 unique videos per hour, saving its marketing team tons of time.

It's worth noting, though: whether you're using Gen AI to create written or visual content, human oversight is still crucial. In a marketing context, human marketers are necessary to polish AI-generated outputs and evaluate them for quality and brand alignment. Together, humans and AI can create hyper-personalized experiences that strengthen customer loyalty and engagement.

3. Accelerate Marketing Processes End to End

Gen AI isn’t just a tool for content creation – it can transform marketing processes from end to end. Your marketing team can use it to:

Brainstorm campaign ideas. Gen AI can evaluate existing campaign ideas or come up with new ones based on the audience details you provide. Then, your marketing team can refine these ideas into polished, on-brand strategies.

Fast-track internal reviews. AI tools can analyze content drafts, providing feedback on clarity, tone, and audience alignment. The benefit: less time on back-and-forth revisions.

Improve SEO. From keyword research to content optimization, AI can support SEO efforts at every stage. It can identify high-performing keywords, suggest meta descriptions, and even identify outdated content, helping teams stay ahead in search rankings.

Audit your content library. Gen AI can review your entire content repository to identify gaps or misalignments. Then, it can update existing content and create new content that meets your audience's unique needs.

With the help of Gen AI, your marketing team can personalize more content and campaigns at scale. What's more, employees can use the time saved to execute strategic initiatives that drive results.

To Embrace Experience AI, Start Small

Hyper-Personalization Requires Flexible Software

1. Deepen Your Audience Analysis and Campaign Strategy

2. Draft Hyper-Personalized Messages (Written and Visual)

3. Accelerate Marketing Processes End to End

To Embrace Experience AI, Start Small

Hyper-Personalization Requires Flexible Software

Gen AI in marketing translates to tangible ROI: 37 percent of orgs that use it report lower costs, and 53 percent say they've seen an uptick in revenue.

Of course, not all Gen AI solutions are made equal. Different tools excel at different tasks (e.g., Perplexity for research, Claude for campaign brainstorming, ChatGPT for content creation, etc.). It's important to choose the right model for the job at hand – and give your team enough flexibility to switch between them without losing efficiency or effectiveness.

That’s where CI&T FLOW comes in. By providing seamless access to various AI tools, FLOW ensures your team has the flexibility needed to choose the best solution for every task. And if you've been keeping up with this blog series, you know that FLOW can help you integrate AI into countless other business processes.

Want to learn more about how CI&T FLOW can revolutionize your marketing strategy? Reach out today and empower your marketing team to achieve true hyper-personalization.

Lucas Persona

Chief Digital Officer, CI&T