The Strategy And Synergy Of AI And Agile Methodologies - Forbes Article By Fabio Caversan

This article was originally posted at Forbes website.

At a moment in time when the value of business agility is becoming clearer than ever, a growing range of diverse brands and businesses are prioritizing agility and engaging in digital transformations. Business agility unlocks greater operational flexibility, more nimble and responsive pivots to new processes or priorities, and smarter and more strategic decision-making — all of which is enormously valuable in an increasingly tech-savvy and competitive professional environment, as discussed in my previous article.

One of the most powerful tools that can be deployed to make that transformation successful is artificial intelligence (AI). AI-powered tools and tech form the backbone of systems and solutions that help companies become more agile. What follows is a brief overview of how agile methodologies emerged and why AI delivers such valuable synergies with agile business.

What’s Old Is New

Agile methodology was popularized and refined by software developers in the early 2000s, but the roots of agile operation actually date back to the 1950s, with Toyota’s development of an innovative production system. Two decades ago, when software engineers began experimenting with new and different ways of developing software, projects and products, the result was a more adaptable and collaborative approach that was producing working software earlier and with higher quality.

Today, the concept of business agility has expanded to describe a company’s ability to compete and thrive in the digital age by quickly responding to market changes and emerging opportunities. Lean and agile principles have been increasingly applied in a range of different industries and contexts, and they’ve been used successfully to address any complex problem that requires the intense cross-functional collaboration of experts.

 

Agile Value

Agility doesn’t just increase speed, efficiency and productivity. The real magic is its ability to reduce waste and help teams work more intelligently, focusing keenly on value delivery and business goals. Agility also helps deal with unpredictable problems and impediments by keeping everything visible, keeping everyone involved and keeping the focus on continuous and incremental improvement.

The most successful applications of agile methodologies rely on small, focused and self-sufficient teams periodically testing and either rejecting or accepting new systems and processes. Progress is made in short bursts, with an ongoing process of testing and troubleshooting ideas ultimately yielding more successful outcomes.

Sometimes, however, larger organizations may struggle to reorganize their traditional structure in a way that minimizes dependencies and optimizes the flow of value of their agile teams. If that is the case, they can find support in commonly accepted good practices for agility at scale that help with aligning and synchronizing multiple teams toward the same business goals. Modern Agile summarizes those guiding principles as:

  • Make people awesome.
  • Make safety a prerequisite.
  • Experiment and learn rapidly.
  • Deliver value continuously.

While there are no silver bullets and each company needs to understand how to best apply and adjust different practices to their context, general best practices include:

• Staying flexible. While it’s helpful to start with a digital “road map,” digital/agile transformations inherently and inevitably include both successes and failures, with empirical, evidence-based results driving the process. The goal is to move forward in a lean manner, focusing on value and reducing waste, and simultaneously introducing new technologies while keeping complexity and uncertainty within manageable parameters.

• Leveraging data. Even the best AI-based systems and solutions depend on your ability to gather and manage critical data. With that in mind, clearly identify the relevant data and key metrics that define your company’s work and will chart its progress as an essential part of the digital transformation process.

• Narrowing your focus. The big picture is important, but the pace of innovation is such that traditional long-term planning doesn’t work well with digital transformations. You need to move quickly — albeit strategically — to execute short- and medium-term plans. The goal is to “see long but act short,” replacing long-term planning with a more flexible long-term vision.

• Prioritizing people. New tech is always thrilling, but successful digital transformations are less about the tech and more about the people using it. This is why it’s important to unlock the human potential of new systems and solutions by putting users first and considering how your teams operate and engage with tools and information.

The AI Intersection

Because agility helps navigate complex problems where the relationship between cause and effect is not necessarily straightforward, agile methodologies are an ideal fit for designing and implementing new AI solutions. The ability to test a hypothesis and, depending on the results, modify the strategy accordingly is invaluable for AI projects that may require a fair amount of research and testing throughout the development.

However, the synergies between agile and AI go both ways, and AI can be used to empower agile squads in several profound and important ways. AI-powered tools and tech can be used for automation, greatly increasing the speed with which different iterations of products and processes are tested and refined. Whether it is analyzing market trends and analytics or delivering real-time feedback and results, AI can provide the most critical ingredient in the agile transformation puzzle: data.

Not only can AI-powered systems and solutions collect data speedily and more efficiently, but they can also organize and process that data in ways that make that data more transparent — and they can make subsequent conclusions that are drawn from that data more obvious.

One of the most exciting aspects about AI-powered tech is that it drives innovation not just in product creation itself and not just in the metrics and models used to make existing products and processes more valuable and more efficient, but also in the structure and operation of the people and institutions who are creating and testing those products and processes. AI tech can allow teams to operate faster and more securely with a higher degree of automated time-saving efficiency.

At a time when agile methodologies have become the gold standard, AI-powered tools and tech can provide invaluable synergies, unlocking game-changing new capabilities and helping to take already flexible and efficient new operational innovations to thrilling new heights.

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