Integrating AI into your software product is the future. Here, we bring you 7 tips that'll help you make it happen.
6 benefits of AI app development
The global AI market is expected to grow to $1.84 trillion by 2030, a 20x increase from its current value.
That’s why AI app development should be a no-brainer.
It’s not all about the money, though.
AI can improve your product and help you better meet your users’ needs.
If you’re still on the fence about integrating AI into your product, let’s discuss some benefits of AI integration that’ll change your mind.
Enhanced user experience
“People ignore design that ignores people.”
This quote by designer Frank Chimero underscores the importance of a good user experience when using a product.
AI app development can help you take your product to the next level.
AI isn’t just about advanced calculations or data analysis.
It’s revolutionizing the way we interact with digital products.
Take personalization, for example.
According to a report by Twilio Segment, 92% of companies are already using AI-driven personalization to drive business growth.
Customers want personalization, too.
66% of customers would stop using a product if their experience isn’t personalized.
That number rises to 75% among Gen Z consumers.
AI can help you deliver an experience that’s tailored to each user’s needs and preferences.
Your users will stick with your product if you understand their unique needs.
Take Netflix, for example.
Netflix uses AI and machine learning to fine-tune and personalize each user’s recommendations.
80% of what Netflix users watch comes from their recommendation algorithms.
Another good example is Spotify and its Discover Weekly feature.
They use machine learning to deliver tailor-made recommendations to each user every week.
These AI-powered recommendations are their competitive advantage and help them deliver a hyper-personalized user experience.
Another good way to enhance your product’s UX with AI is to use it to analyze your users’ feedback.
First, you should create a feedback loop so you continuously gather user feedback.
Then, you can use AI to analyze user behavior and the feedback you’ve gathered to identify areas for improvement.
This way, you’ll ensure you’re always on top of your users’ needs.
One other way you can improve your product’s UX is by integrating a customer service AI chatbot.
They’ll help your users quickly solve the most common problems they might have with your product.
This’ll improve their satisfaction with your product and help you retain them.
A good option for this is using an off-the-shelf machine learning model, like one of OpenAI’s models.
You can also fine-tune the base model for your specific use case and increase its accuracy.
Regardless of which option you choose, AI is a powerful tool that can deliver value to your users and significantly improve their experience.
Improved product efficiency
“The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency.
The second is that automation applied to an inefficient operation will magnify the inefficiency.”
This quote by Bill Gates underscores how automation and AI can’t improve efficiency on their own.
Software products are no exception.
So, how do you improve your app’s efficiency with AI?
The first step is optimizing your app development process with AI.
Behind every software product is a labyrinth of operations, processes and tasks.
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With AI, you can navigate it more quickly and improve your operational efficiency.
Just that on its own will help make your product more efficient.
You’ll be able to roll out updates and new features much faster, helping you keep your product fresh.
The most important benefit AI tools bring is automating routine tasks which take up a lot of your engineers’ time.
Automating them with AI will allow them to focus on more important tasks.
One such task is coming up with ways to integrate AI into your product to directly improve its efficiency.
So, how can you do that?
Let’s say you have a software product for writing.
You can use AI to power a number of features, such as predictive text and context-aware grammar correction.
Grammarly, one of the leading writing software companies, extensively uses AI techniques, such as:
- Machine learning
- Natural language processing
- Deep learning
These help them improve their product’s efficiency and their users’ satisfaction.
Another interesting use case of AI to improve product efficiency is automatic image tagging in photo storage apps.
It doesn’t have to stop there.
AI can then automatically categorize and sort photos into albums like:
This’ll improve your product’s efficiency and deliver extra value to your users.
And that’s the best way to retain users and ensure your product’s success.
Every decision you make about your product should be backed up with solid data.
AI will help you quickly and efficiently analyze huge amounts of data to inform your decision-making.
As Clive Humby, British data scientist, said: “Data is the new oil. It’s valuable, but if unrefined, it cannot really be used.”
Think of AI as a refinery for data.
It can extract information from raw data and turn it into usable knowledge which you can use to make better product decisions.
The numbers back that up.
A Harvard Business Review survey of executives showed that data-driven companies are more profitable.
Respondents who rated themselves higher at getting business value from AI-driven data analytics performed better than those who rated themselves lower.
source: Google Cloud
They scored significantly higher across key business metrics, such as:
- Operational efficiency (81% vs. 58%)
- Revenues (77% vs. 61%)
- Customer loyalty and retention (77% vs. 45%)
These numbers show the impact using AI for data-driven decision making can have on your product’s success.
Another way you can use AI-driven data analysis is by analyzing your users’ behavior and feedback on your product.
You’ll get a clear picture of how your users feel about your product and areas in which you need to improve.
It’ll also be able to find patterns in the data you might’ve missed.
This’ll allow you to make better decisions that better meet your users’ needs.
And the best part of using AI for data-driven decision-making?
It’s objective and unbiased by design.
This means you can be confident in your decisions.
But, make sure that the data you gather for analysis is meaningful and accurate.
As capable as it is, AI is still vulnerable to the classic “garbage in, garbage out” concept.
As long as you make sure the data you use is correct, you’ll get good results and improve your product with data-driven decision-making.
And using AI to analyze data makes implementing it much easier.
The software product landscape is always evolving.
To address challenges and take advantage of new opportunities, your product needs to be scalable.
AI can help you achieve that.
Take a look at Dropbox, for example.
Dropbox uses AI to handle and sync the millions of files their users store on their servers.
They’ve also introduced customer-facing AI features that can summarize the contents of text files with a single click.
AI helps Dropbox scale their operations and smoothly handle the huge amount of data their users store.
But, what are some specific ways you can use AI to scale your app?
One good way to use AI is optimizing resource management.
AI can predict when you might need more resources, like server capacity.
It uses historical data and current traffic patterns to automatically allocate resources where they’re needed.
Machine learning models can also predict traffic surges and respond accordingly to ensure the optimal use of resources.
They can distribute network traffic across multiple servers to balance the load.
This way, no single server will be overwhelmed.
Efficiently using resources will help you more easily scale your product.
Another way AI can help you scale your product is by automating your engineers’ routine tasks with coding assistants like Github Copilot.
Your engineers won’t just work faster.
With AI automating repetitive tasks, they’ll have more time to come up with scaling strategies and other ways to improve your product.
Engineers who use Github Copilot agree that it helps them be more productive, as you can see in the image below:
source: Github Blog
All this will make scaling your product faster and easier.
AI tools can also make your code more efficient.
You can use them to refactor and optimize your codebase,
Clean and efficient code will make scaling your product easier.
Opening up new revenue streams
“Innovation distinguishes between a leader and a follower.”
With the rise of AI, this quote by Steve Jobs is more relevant than ever.
AI can help you open up new revenue streams for your product and turn you from a follower into a leader.
The numbers back that up.
Take a look at the exact figures below:
And these are just figures related to the adoption of AI tools.
Integrating AI capabilities into your software product will result in even larger revenue increases.
Take Adobe, for example.
Their new AI and machine learning tool, Adobe Sensei, helped Adobe carve a niche in personalized marketing automation.
It also added AI-powered features to their existing products, like Photoshop.
So, not only did they open up new revenue streams but they also helped drive users to their existing products.
IBM is another good example.
They’ve turned Watson, their proprietary AI model, into an enterprise-ready AI and data platform called Watsonx.
They’re now a market leader in providing AI solutions for businesses, working with some of the biggest companies in the world like General Motors and GSK.
But, what are some ways you can use AI to open up new revenue streams for your product?
A simple way to start is by upgrading existing features with AI.
This’ll help you attract new customers and help you retain existing ones.
You could also add AI-exclusive features, like AI chatbots or predictive analytics, which your users might be willing to pay a premium for.
Another good way to open up new revenue streams is by using AI for personalized marketing.
If you operate on a freemium model, AI can identify users who are most likely to convert from free to premium.
Then, it can target them with tailored incentives.
You can also use AI in market research to identify emerging user needs.
This’ll help you prioritize which features to add to your product and which updates you should make.
“The only truly secure system is one that is powered off, cast in a block of concrete and sealed in a lead-lined room with armed guards.”
This quote by Gene Spafford, computer security expert, reminds us that a 100% secure system doesn’t exist.
Still, you can use AI to significantly improve your security.
This is especially important as cybercrime is expected to surge in the coming years.
The global cost of cybercrime is expected to rise from $8.44 trillion in 2022 to $23.72 trillion in 2027.
On average, the cost of a cyber breach in 2022 was $4.35 million.
These figures are a compelling reason to invest heavily in improving your organization’s cybersecurity.
And AI capabilities can help you take it to the next level.
Take Darktrace, for example.
Their AI-driven Enterprise Immune System technology detects and counters cyber threats in real time.
Another good example is CrowdStrike’s Falcon platform.
It uses AI machine learning models to spot malicious software patterns and protect from cyber threats.
But, how exactly does AI improve your product’s security?
The main reason is that it’s proactive, not reactive.
This means that it can predict potential vulnerabilities and threats even before an attack happens.
The main strengths of AI are its data analysis capabilities and pattern recognition.
It can analyze your product’s entire codebase and identify vulnerabilities you might have missed.
And it quickly spots suspicious behavior and reacts to threats in real-time.
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Also, AI can learn and adapt after every security incident.
So, even if a breach does occur, it can ensure that it doesn’t happen again.
A good tip for implementing AI-driven cybersecurity systems is to adopt a multi-layered security approach.
You should analyze everything from user behavior to scanning incoming emails for phishing attempts.
By doing that, you’ll cover all possible avenues of attack and security vulnerabilities.
This’ll make your product as safe as it can be and increase user trust.
AI app development benefits: conclusion
AI app development will help you take your product it to the next level.
With AI, you’ll be able to better meet your users’ needs and improve your product.
So, what are some benefits of integrating AI into your software product?
To recap, they are:
- Enhanced user experience
- Improved product efficiency
- Data-driven decision making
- Opening up new revenue streams
- Improved security