In today’s fast-paced society, organisations must adapt swiftly to stay competitive. Agility has become an essential requirement for organisations to thrive, and Artificial Intelligence (AI) is becoming an ever-more powerful ally in achieving this agility.
AI-driven tools are reshaping the way teams collaborate, innovate, and deliver results by introducing automation, data-driven insights, and advanced risk and issue management capabilities. These tools are also helping to improve workflows and reduce costs.
With solutions such as Jira with machine learning, GitHub Copilot, Chat GPT and Trello’s Butler, businesses are transforming their operations and embracing a future that is both efficient and resilient. How are they doing that? Let’s explore these and other key tools below.
The Role of AI in Enhancing Business Agility: Tools and Their Uses
AI tools empower organisations to respond quickly to changing conditions, streamline operations and foster innovation. These tools facilitate:
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Risk and Issue Management: Platforms such as Jira integrate machine learning to improve task prioritisation, resource management, and workflow automation. Jira helps teams to predict task completion times based on historical data and automatically assigns tasks to the team members best suited to handle them. Predictive analytics help anticipate potential project risks and bottlenecks, allowing teams to address challenges before they escalate. This proactive approach ensures smoother operations and timely delivery. Global technology consultancy firm Accenture uses Jira with machine learning-powered add-ons to streamline project management and sprint planning. The tool allows faster decision-making and better resource allocation, allowing consultants to adjust project timelines dynamically in response to client needs.
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Business Costs Reduction: AI reduces manual effort and optimises resource allocation. Automation leads to a reduction in operational expenses, enabling organisations to redirect savings into innovation and growth.
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Data-Driven Insights: AI tools analyse vast amounts of data, uncovering trends and generating insights that can be immediately acted upon. Salesforce Einstein for example provides AI-driven insights into customer behaviour, sales forecasts, and marketing campaigns. It strengthens customer engagement and fosters loyalty by personalising customer interactions and providing tailored recommendations. These insights improve decision-making techniques by empowering decision-makers to adjust strategies in real time and remain aligned with the needs of their market. Tableau is another tool that integrates AI to deliver actionable visual analytics. Its ability to process and visualise large datasets empowers organisations to optimise operations.
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Deep Learning: Advanced tools such as GitHub Copilot leverage deep learning to assist developers in creating high-quality code, reducing errors, automating repetitive programming tasks, and even predicting bugs. This tool also accelerates software development cycles, enabling teams to remain nimble in rapidly evolving markets. Language learning platform Duolingo uses Copilot to write boilerplate code, which speeds up development for routine or repetitive tasks. This allows engineers to focus on higher-level application logic and innovations in their adaptive learning algorithms. The tool also helps Duolingo engineers quickly prototype new features for their mobile and web applications, reducing the time it takes to move from concept to implementation. By suggesting code snippets and best practices, Copilot helps the team avoid common coding errors too. The tool can even help onboard new team members by helping them understand and adapt to Duolingo's codebase faster. By integrating GitHub Copilot into its workflows, Duolingo improves efficiency and empowers its developers to focus on creative problem-solving rather than manual coding tasks.
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Administrative processes: ChatGPT is a tool that generates human style conversational responses and allows users to refine and steer a conversation towards a desired length, format, style, level of detail and language. Financial services company Morgan Stanley uses it to provide contextual insights to help advisors tailor their advice to individual client needs. It also helps them summarise lengthy documents. Trello’s Butler is another AI innovation that automates administrative processes, such as sending reminders, updating records automating repetitive task assignments and managing deadlines, thereby simplifying team collaboration and freeing up valuable human resources for creative and strategic tasks. Global marketing agency Ogilvy uses this tool to automate routine project management tasks such as moving cards between lists when deadlines are met or sending reminders to team members for overdue tasks. For example, when a new client onboarding checklist is completed, Butler automatically triggers the creation of a content production board with pre-configured templates. Automation allows the team to focus on creating campaigns rather than managing workflows, enabling faster client turnaround times and increased responsiveness to client demands.
Examples of AI-Driven Automation in Action
Automation is a cornerstone of AI’s impact on business agility. Here are just some examples of organisations who are using AI to achieve great things!
Evaro
At the Agile Business Consortium’s Agile Business Awards 2024, UK-based medical startup Evaro showcased the organisation’s multi-million pound saving AI solution to improve access to everyday healthcare.
By partnering with trusted brands to provide AI-driven, asynchronous consultations and private prescription services, Dr Wenbar, co-founder and CEO, detailed how the organisation is helping to address the health issues typically handled by General Practitioner doctors (GPs) in the UK.
She explained: “Patients face a frustrating maze of appointments, time off work, sitting in waiting rooms and running around to get their prescriptions. I knew there had to be a better alternative, so we are building a platform that empowers individuals to manage their health in a simpler, more convenient, self-serve way.
“We hand over the technology to these big brands and then we ask patients a series of questions – all asynchronous – no video calls, no phone calls. We review the answers to their consultations, in the form of questionnaires. We issue the prescription and then we fulfil it from our warehouse pharmacy.
“We handle the whole chain and try to make as much of it self-service as possible, keeping behind the regulators that we have to appease as well and also making sure it’s incredibly safe for patients.”
Dr Wenbar added: “The affordable services Evaro provides offer an alternative to lengthy wait times for GP appointments and the high costs of private healthcare.
“To date, we’ve supported over 350,000 patients and saved the NHS almost 11 million pounds!”
Zurich Insurance Group
Another prime example of automation in practice is Zurich Insurance Group, which employs intelligent bots to process personal injury claims. This approach significantly reduces processing times and improves accuracy, thereby enhancing customer satisfaction. By eliminating the need for manual intervention in routine tasks, businesses can dedicate resources to innovation and strategic projects.
Tesla
Tesla employs AI in its highly automated production lines. From assembling vehicles to quality checks, Tesla uses machine learning to monitor and adjust processes in real time. This automation helps maintain precision, reduce waste, and speed up production cycles.
Netflix
Netflix utilises AI to automate and enhance its recommendation engine, tailoring content suggestions for individual viewers. AI also plays a role in content production by analysing audience preferences to predict what types of shows or films will be successful, thus automating parts of the creative decision-making process.
UPS (United Parcel Service)
UPS’s On-Road Integrated Optimisation and Navigation (ORION) system leverages AI to optimise routes for delivery drivers. By analysing traffic, weather, and package data, ORION reduces fuel consumption, delivery times, and operational costs.
Coca-Cola’s Marketing Automation
Coca-Cola leverages AI-driven automation for marketing campaigns. AI tools analyse consumer data to identify trends, predict behaviour, and create personalised marketing content. Automation tools also manage distribution channels to ensure campaigns reach the right audiences.
Transitioning to AI-Fuelled Agility
Becoming an AI-driven organisation is a phased journey, often categorised into three stages:
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Assisted Intelligence: AI tools support simple tasks, enhancing efficiency and consistency.
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Augmented Intelligence: Humans and AI collaborate, with AI amplifying human decision-making through analytics and recommendations.
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Autonomous Intelligence: AI operates independently, managing complex processes and freeing humans to focus on creative and strategic pursuits.
As organisations embrace these stages, they unlock new levels of productivity, cost efficiency, and adaptability, enabling them to remain competitive in a rapidly evolving environment.
Challenges in Integrating AI into Business Agility
Although there are many benefits, integrating AI into business agility practices does pose some challenges as well. Employees may resist adoption due to fears of AI taking over their jobs, while organisations may face difficulties aligning AI tools with existing workflows. To overcome these hurdles, businesses must:
- Foster a culture of innovation by positioning AI as a partner rather than a replacement
- Invest in reskilling and upskilling programs to prepare employees for an AI-enhanced workplace
- Ensure ethical AI implementation through guardrails that safeguard data privacy and alignment with organisational goals
The Future of AI-Powered Agility
The future of AI-powered business agility is promising. In 2025, AI will transition from a tool to a virtual co-worker capable of managing tasks autonomously. For instance, generative AI will support inclusivity by assisting individuals with dyslexia or ADHD to communicate more effectively. Additionally, AI-powered translation tools will break down language barriers, fostering diverse and collaborative workplaces.
Beyond the workplace, AI’s environmental applications, such as real-time pollution monitoring, highlight its broader societal impact. These capabilities demonstrate AI’s potential to drive innovation and address global challenges simultaneously.
AI as the Cornerstone of Agility
AI-powered tools are revolutionising the way organisations operate, enabling them to adapt, innovate, and thrive in a rapidly changing world. By integrating solutions such as Jira, GitHub Copilot, and Trello’s Butler, businesses can enhance risk and issue management, reduce costs, and harness data-driven insights for strategic advantage. As the synergy between AI and agile practices continues to evolve, organisations that embrace this combination will not only remain competitive but lead the way in shaping the future of work and innovation.
Read more: The role of AI in project management: opportunities and challenges
Generative AI : Disrupting Traditional Marketing
Please note blogs reflect the opinions of their authors and do not necessarily reflect the recommendations or guidance of the Agile Business Consortium.