DEVOPSdigest

DEVOPSdigest invited experts across the industry — consultants, analysts and vendors — to comment on how AI can support the software development life cycle (SDLC). Part 3 of this series covers advantages gained by leveraging AI tools in software development.

In Part 3, the experts discuss the business benefits of AI in dev, and the advantages that ultimately lead to bottom-line gains. Many of these advantages overlap, but the list provides a detailed overview of the many ways utilizing AI in the SDLC can positively impact development and the business.

DEVELOPER PRODUCTIVITY

Automation is undoubtedly the greatest advantage of AI, creating a chain of positive impacts that begins with developers' productivity and trickles down to the company's bottom line. Automating repetitive and time-consuming tasks frees developers to focus on more complex and creative work, leading to faster development cycles and quicker time to market for new products and features. AI's contribution helps reduce development costs and improve overall business profitability.
Dotan Nahum
Head of Developer-First Security, Check Point Software Technologies(link is external)

Today, getting more productivity out of engineering teams is a priority for most companies, and this is where a lot of AI's promise comes into play for developers. Teams today are lean and strapped for resources, so anything AI can do to remove some of that pressure is vital. Using AI to assist with writing code is a big part of this, but another example is using AI to improve the PR process by catching obvious bugs or issues. Or even fielding common requests in Slack, helping developers find previous discussions across different channels, or digging through documents. This avoids context switching, which quickly interrupts developers' workflows.
Michael Webster
Principal Software Engineer, CircleCI(link is external)

Developers will be the first to admit that only a small part of their job is actively writing code. So much of it is debugging, researching, planning, and deploying. AI provides a huge boost to developer productivity because those tasks can be significantly accelerated. For example, AI can suggest code patterns rather than hunting the internet for samples. In turn, this helps easily identify and mitigate issues and errors. All of this results in higher output and increased quality from developers, enabling them to drastically increase their bottom-line input.
Jeff Hollan
Head of Applications and Developer Platform, Snowflake(link is external)

Developers are excited about being faster and more productive so they can focus more on what else can they do. They can spend more time doing complex design or getting complex features out sooner.
Neha Goswami
Director of Engineering for Amazon Q Developer, AWS(link is external)

According to McKinsey(link is external), AI is improving productivity by cutting down the time spent on generating and documenting code by nearly one half, revealing that AI coding assistants can be formidable assistants for quick fixes and partnering on core programming tasks. Pieter Danhieux
Co-Founder and CEO, Secure Code Warrior(link is external)

Increased productivity is one of the greatest advantages. Problems that might historically take days or hours could take an engineer using AI tools minutes to solve.
Sterling Chin
Senior Developer Advocate, Postman(link is external)

I recently wrote a script to pull data out of our CI/CD pipeline and uploaded it to a data lake. With ChatGPT's help, what would have taken my rusty Python skills eight to ten hours ended up taking less than two, an 80% productivity boost!
Marcus Merrell
Principal Test Strategist, Sauce Labs(link is external)

COUNTERPOINT: I think the savings are not as great as others do. Still, 20% is important.
Mike Loukides
VP of Emerging Tech Content, O'Reilly Media(link is external)

DEVELOPMENT VELOCITY

AI accelerates the software development process by automatically generating reusable code components, freeing up developers to move beyond repetitive coding work and focus on higher-value challenges.
David DeSanto
Chief Product Officer, GitLab(link is external)

AI helps increase the velocity of software development by automating several aspects of coding through features like code auto-completions, code editing through natural language, and chat for any kind of coding-related topics — both tactical code changes and high-level design and architecture changes.
Raman Sharma
CMO, Sourcegraph(link is external)

In one word: speed. Developers can fast-track many basic tasks. Sometimes, looking up the syntax for a complex CLI call takes minutes, whereas AI can provide the needed command suggestions as the developer types.
Mathieu Bellon
Senior Product Manager, GitGuardian(link is external)

In some of our initial work to roll out AI-powered automation in these areas, we've seen software development processes speed up by as much as 90%.
Marco Santos
Co-CEO, GFT Technologies(link is external)

STARTING NEW PROJECTS

AI coding assistants can move projects forward faster and provide developers with a jump start by helping them figure out where they need to begin. With AI, Proof Of Concept (POC) projects can be done way faster than before in order to explore new approaches that can (or can not) become production code. As long as a developer can input their preferred language and their specific requirements, AI can help provide an approach to solving a problem and guide developer teams through challenges at a faster pace than before.
Jonathan Vila
Developer Advocate, Sonar(link is external)

AI's greatest contribution to society is arguably its ability to accelerate learning and solve problems. Treating AI tools like a brainstorming bot and having back-and-forth conversations with them helps expedite the learning and exploration process when building new things, instead of taking a lot of time to explore various websites.
Randall Degges
Head of Developer & Security Relations, Snyk(link is external)

PROBLEM SOLVING

With AI in software development, users can leverage automatic transformations and data handling to support problem-solving. This allows teams to tackle more complex issues and make more valuable contributions to the team.
Eoin Hinchy
CEO and Co-Founder, Tines(link is external)

AI is very good at pattern matching and as a result, automates away the coding problems that have been solved thousands of times by other developers.
Raman Sharma
CMO, Sourcegraph(link is external)

CODE QUALITY

Code quality is improved with data driven insights when using AI to support development.
Anand Kulkarni
CEO, Crowdbotics(link is external)

Improved code quality and bug reduction: AI-powered code assistants can analyze large code datasets to produce code with fewer potential errors and follow best practices around security, efficiency, and design patterns. This results in faster debugging and higher overall code quality.
David DeSanto
Chief Product Officer, GitLab(link is external)

AI enhances code quality by consistently enforcing best practices and identifying potential bugs early, leading to more reliable and maintainable software.
Rahul Pradhan
VP of Product and Strategy, Couchbase(link is external)

AI can review code to identify common errors in real-time as developers are coding and make suggestions on how to fix any mistakes. In addition to finding errors, AI can offer suggestions for code optimization and security improvements. This results in companies being able to build more reliable, efficient and secure applications.
David Brault
Product Marketing Manager, Mendix(link is external)

USER EXPERIENCE

AI is creating massive time savings and efficiency gains across the software development lifecycle that have, in turn, introduced benefits that trickle all the way down to the end user. This is because of its ability to automate inefficient processes that have plagued developers for decades, and enable them to spend their time solving more complex problems and focusing on big picture innovation.
Marco Santos
Co-CEO, GFT Technologies(link is external)

According to McKinsey(link is external), research shows that 71% of consumers expect companies to deliver personalized interactions — and 76% get frustrated when this doesn't happen. In order to meet these demands, organizations can look to AI tools to support development and foster end-user experience improvements.
Dana Lawson
CTO, Netlify(link is external)

CUSTOMER SATISFACTION

AI can be leveraged to avoid bottlenecks for code fixes which enhances both the developer and customer experience.
Dana Lawson
CTO, Netlify(link is external)

Many software engineering teams have a big concern that their engineers spend a lot of time on things that are necessary but don't really produce net new customer value. Automation through AI takes care of such tasks and allows developers to take on more interesting projects that can have a direct customer impact.
Raman Sharma
CMO, Sourcegraph(link is external)

COLLABORATION

AI can enhance cross-team collaboration by providing insights and recommendations that result in more informed decision-making. Ultimately, these advantages lead to faster delivery times and higher-quality software products.
Ed Frederici
CTO, Appfire(link is external)

Streamlined workflows mean fewer roadblocks and bottlenecks. AI facilitates cross-team collaboration and ensures that tasks flow smoothly from one stage to the next, reducing friction.
Eoin Hinchy
CEO and Co-Founder, Tines(link is external)

AI coding assistants act as extra team members, providing recommendations and completing repetitive tasks to reduce the workload for human developers. This allows developers to spend more time collaborating on solving complex problems, enhancing the coding journey for every developer.
David DeSanto
Chief Product Officer, GitLab(link is external)

CREATIVITY

By automating mundane and repetitive tasks, developers can devote more time to the creative aspects of their work.
Ed Frederici
CTO, Appfire(link is external)

INNOVATION

As a company, you have a highly intelligent workforce of developers, and today they are spending so much time maintaining code and testing, when developers could be spending time on higher value tasks. The overall advantage with AI-powered software development assistants is that you're freeing up your developers to do higher value tasks.
Neha Goswami
Director of Engineering for Amazon Q Developer, AWS(link is external)

A technology that reduces development time while increasing quality is the holy grail for a software team. AI adoption is enabling teams to focus on innovation rather than getting bogged down by tedious, manual tasks. It should be about enhancing the capabilities of developers and testers so they can push the boundaries of innovation.
Todd McNeal
Director of Product Management, SmartBear(link is external)

AI can help in decision making by acting as a "second reviewer" to help develop and refine a project plan, making it stronger and more efficient, allowing teams to ideate faster on new product ideas.
Shourabh Rawat
Senior Director, Machine Learning, SymphonyAI(link is external)

DEMOCRATIZATION

AI reduces the barriers to entry for code development. Some may argue that this is not necessarily good for valid reasons, such as code quality and a lack of knowledge about what the code is achieving. But from a bigger-picture perspective, it allows entrepreneurs, businesses, and teams to do more things they otherwise may not have the budget or skill to do.
Karl Cardenas
Director, Docs & Education, Spectro Cloud(link is external)

Software development has traditionally followed an apprenticeship model where skills are passed down from senior to junior developers through mentorship. This was especially true when people were mostly in physical offices — it was almost ingrained in the culture of teams sitting next to each other. AI has the potential to augment this mentorship model by acting as a coach or guide for less experienced developers. That being said, AI is nowhere near replacing the human touch it takes for true mentorship, but it can help answer questions or let junior folks explore topics in open-ended ways. This democratization of development is particularly powerful, allowing more people to engage in software creation without needing years of experience.
Michael Webster
Principal Software Engineer, CircleCI(link is external)

NEW DOMAINS

For experienced developers, AI opens up new domains. A Java developer can easily learn and write Scala. Then, they can branch into DevOps. Product Managers can improve their SQL skills. For professionals with the aptitude and curiosity, AI gives them superpowers. This helps remove bottlenecks for teams composed of specialists — an iOS developer no longer needs to wait on an API developer to expose a new endpoint if they can prompt an LLM to write code and issue a pull request.
Sakshi Garg
Head of Engineering, Hydrolix(link is external)

DEVELOPER EXPERIENCE

AI assistants free developers from everyday tasks such as debugging failed builds and providing suggested fixes, leading to a differentiated and more rewarding developer experience.
CTO, Netlify(link is external)

DEVELOPER RETENTION

Developers want to use AI technologies, so it's good for recruitment and retention
Patrick Doran
CTO, Synchronoss(link is external)

AI encourages teams to innovate and experiment with new workflow possibilities, which fosters a culture of continuous improvement and learning, which is crucial for long-term engagement and loyalty.
Eoin Hinchy
CEO and Co-Founder, Tines(link is external)

With increased efficiency through AI comes the opportunity for developers to mitigate future burn out, thus making developer retention easier and potentially saving significant money on recruitment.
Pieter Danhieux
Co-Founder and CEO, Secure Code Warrior(link is external)

TIME-TO-MARKET

Companies can achieve faster time-to-market by automating various parts of the development lifecycle, and cost savings can be realized through automation and process optimization.
Ramprakash Ramamoorthy
Director of AI Research, ManageEngine(link is external)

Developers will be able to quickly prioritize their work, automate traditionally manual tasks, test their work faster than ever before, and get intelligent suggestions throughout the development process to produce enterprise-ready applications more quickly.
Matt Healy
Director of Product Marketing, Intelligent Automation, Pega(link is external)

Efficient development cycles allow for quicker product releases, enabling your company to "outrun" competitors and potentially generate revenue sooner.
Patrick Doran
CTO, Synchronoss(link is external)

One of the most immediate benefits of AI in development is the significant increase in productivity. AI automates routine tasks like code generation, testing, and debugging, enabling developers to focus on more complex, creative work. This helps speed up development cycles and time-to-market, giving companies a competitive edge.
Rahul Pradhan
VP of Product and Strategy, Couchbase(link is external)

UPDATES

By automating deployment tasks and mitigating human error, AI can help streamline the development process, leading to more consistent releases and a quicker time to market for patch updates.
Scott Willson
Head of Product Marketing, xtype(link is external)

AGILITY

AI essentially makes every developer the best developer they can possibly be, optimizing their experiences while producing better outcomes at the same time. This ultimately helps an organization be more agile and adaptive than ever before.
Matt Healy
Director of Product Marketing, Intelligent Automation, Pega(link is external)

DECISION-MAKING

AI can analyze vast amounts of data to offer insights that humans might miss, leading to better decision-making. In the end, it's all about working smarter, not harder, which can reduce costs and get your product to market quicker.
Casey Ciniello
App Builder, Reveal and Slingshot Senior Product Manager, Infragistics(link is external)

Behind the scenes, AI can support teams outside devs. For example, AI helps product teams by providing insights into development trends and performance metrics. Senior management can see the results by turning to AI for detailed insights into resource utilization, allowing for better-informed decision-making and more efficient resource allocation. Marketing gets its slice of the pie by using AI to personalize user experiences, provide more targeted recommendations, and deliver faster and more efficient customer support, increasing customer satisfaction and loyalty.
Dotan Nahum
Head of Developer-First Security, Check Point Software Technologies(link is external)

COST SAVINGS

The reduction in errors and technical debt translates into substantial cost savings over the long term.
Rahul Pradhan
VP of Product and Strategy, Couchbase(link is external)

The main advantage is developer productivity. Companies' largest expense is payroll and software engineers are expensive. Any money invested in making those engineers more productive pays off big time.
Jeremy Burton
CEO, Observe(link is external)

The use of AI in development reduces the need for additional hiring and training, leading to significant cost savings.
Tom Hodgson
Innovation Tech Lead, Redgate(link is external)

Go to: Exploring the Power of AI in Software Development - Part 4: Challenges