AI Agents: 7 Practical Ways They Transform Business Operations

AI agents supporting enterprise decision-making

AI agents are rapidly becoming a core component of enterprise AI strategies. What began as fascination with large language models (LLMs) has evolved into strategic conversations about AI agents — autonomous systems that go beyond generating responses to acting on business objectives, orchestrating workflows, and delivering outcomes. In 2026, enterprises are no longer debating whether AI matters; they are now asking how to make it work at scale with governance, measurable ROI, and operational integrity.

AI agents are AI-driven systems designed to plan, decide, and act across business workflows. Unlike traditional automation tools, AI agents can adapt to changing conditions, interact with multiple systems, and support human decision-making in real time.

But in this transition, many organizations struggle to separate hype from reality. Leaders need a rigorous, capability-based framework to evaluate what distinguishes true AI agents from traditional automation and uncoordinated Generative AI tools, and how to deploy them responsibly for maximum impact.

What We Mean by AI Agents

At a practical level, AI agents are software systems capable of planning, decision-making, and executing multi-step tasks across systems and data sources with varying degrees of human supervision. In contrast to traditional automation — which follows pre-defined rules — AI agents can interpret context, reason about goals, adapt as conditions change, and interact with systems and humans in more fluid ways.

Importantly, the term “agent” is not marketing fluff but reflects a distinct class of system behavior — capable of setting and pursuing goals, initializing and adjusting workflows, and integrating with enterprise infrastructure at scale.

Seven Capabilities That Define High-Impact AI Agents

Here is a capability framework grounded in current adoption patterns, analyst forecasts, and enterprise needs:

1) Autonomous Planning & Goal-Oriented Execution

True AI agents translate strategic intent into operational steps. They don’t just respond to commands — they break higher-level goals into executable actions, manage dependencies, and adjust execution as conditions evolve. This is the hallmark that distinguishes an “agent” from an advanced assistant.

Enterprise value: Reduced oversight for routine decisions, faster cycle times, and more predictable execution.

2) Real Workflow Ownership

Agents must be able to own an end-to-end workflow, not just automate isolated tasks. In practice, this means:

Maintaining context across steps
Detecting issues and adjusting plans
Escalating to humans only when confidence or governance thresholds demand it

This pattern — sometimes described as bounded autonomy — is increasingly the standard, as fully unconstrained autonomy remains impractical for most enterprise functions.

Enterprise value: Lower operational friction, fewer manual interventions, and improved throughput.

3) Multi-Model & Multi-Data Competence

High-impact agents must process diverse data types — structured records, unstructured text, documents, images, audio, and real-time signals — and synthesize them into coherent decisions. Traditional automation cannot interpret non-structured inputs at scale.

Enterprise value: Broader applicability across customer service, compliance, supply chain, and more.

4) Deep Integration with Enterprise Systems

Capabilities are meaningless if an agent cannot interact with the enterprise ecosystem — CRM, ERP, workflow tools, identity systems, reporting platforms, and security layers. Technology architectures that support seamless API-level access and data integration are prerequisites for value realization.

Enterprise value: Less technical friction and higher rates of adoption.

5) Multi-Agent Orchestration

The future is not a single all-purpose agent, but ecosystems of specialized agents coordinated to achieve complex outcomes. Leaders increasingly deploy multi-agent ecosystems, where orchestration layers manage task handoffs, priorities, and governance.

Enterprise value: Modularity, reliability, easier troubleshooting, and domain-specific specialization.

6) Accountability & Outcome Measurement

Forward-looking enterprises are shifting to an Outcome as Agentic Solution (OaAS) model — contracting not for tools but for delivered outcomes. This reframes agent deployments around measurable business results rather than technical capabilities alone.

Enterprise value: Clear ROI, predictable value capture, and reduced vendor lock-in.

7) Trust, Security, and Governance

Agents operate on sensitive data and systems; without robust governance, they introduce risk. Trustworthy deployment requires:

Auditability and traceability
Role-based access controls
Human governance guardrails (confidence thresholds, human-in-the-loop for exceptions)

Analysts consistently highlight governance as a critical adoption bottleneck.

Enterprise value: Controlled risk, stakeholder confidence, and compliance alignment.

Current State of Adoption and Enterprise Trends

Analyst forecasts underscore both opportunity and caution:

Market trajectory: Gartner predicts ~40% of enterprise applications will embed task-specific AI agents by the end of 2026, up sharply from under 5% today.
Adoption maturity gap: Surveys show many organizations experimenting with agents today, but few have scaled them beyond pilots.
Automation vs. Agentic AI: Autonomous agents are increasingly seen as digital coworkers rather than simple tools — capable of handling complex workflows in sales, customer service, and operations.
Investment & security focus: Enterprise spending on agentic tooling and governance platforms is rising as cybersecurity concerns broaden with agent deployment.

According to McKinsey, AI agents are increasingly used to automate complex workflows and support decision-making at scale.Gartner predicts rapid adoption of AI agents across enterprise software platforms.

AI agents play a central role in modern AI transformation initiatives.

These signals point toward 2026 as a transitional year — moving from experimentation to operational adoption for well-governed, outcome-oriented agentic deployments.

Pitfalls to Avoid: Insights from Early Enterprise Deployments

Even with promise, agentic AI is not a silver bullet. Key risks include:

Hype and “agent washing” — many vendors rebrand traditional assistants as agents without true autonomous capability.
Weak data foundations — poor data quality undermines autonomous decision-making.
Insufficient governance — unbounded autonomy leads to unpredictable actions.

A disciplined strategy — starting with clear value hypotheses, pilot governance frameworks, and iterative scaling — is essential.

Implications for Business Leaders

AI agents are redefining how work gets done. Organizations that succeed will:

Prioritize outcomes, not tools. Embed agent success metrics into commercial KPIs.
Invest in integration platforms and data readiness. Technical foundations matter.
Build governance models upfront. Security, explainability, and human-in-the-loop models are non-negotiable.
Upskill the workforce. Leaders must blend technical and functional expertise to co-design safe, reliable agentic processes.

iExcel’s Role in Your AI Journey

At iExcel, we help organizations transition from experimentation to industrialized agentic AI deployment. Our services include:

Strategic AI road-mapping aligned to business outcomes
Agent architecture, integration, and governance build-out
Executive and operational AI training to drive adoption and trust

We equip clients not merely to deploy AI agents — but to capture measurable business value from them.

Conclusion: From Promise to Performance

AI agents are poised to become foundational components of the enterprise technology stack. But realizing value requires discipline, governance, integration, and outcome focus. Organizations that adopt with rigor — not just excitement — will reap transformative benefits in productivity, decision-making speed, and competitive differentiation.

Why the Best Custom Software Starts With Stories, Not Tools

custom software development based on business workflows

How understanding workflow and requirements transforms software success in 2026

The Day We Lost a Million Dollars on Tools

Call it what you want — a lesson, a setback, a turning point — but what happened with one major software project early in my consulting career stays with me today.

A global business unit had made every common mistake: they had picked the shiny stack, brought in the newest framework, and built dozens of beautiful UI screens. They were sure they had tech edge.

But six months in, they couldn’t integrate with their core systems, key users couldn’t perform basic tasks, and the backlog of change requests was exploding.

Why?

Because nobody had actually mapped how real work flowed through their organisation.

It was software built for technology’s sake — not for the people and processes actually driving value.

Too many software teams focus first on tools, interfaces, or frameworks. Yet, that project’s failure is far from unique — it reflects a persistent truth in software engineering:

Software succeeds not because of tools, but because it reflects workflow and requirements.

What does that mean in practice? Let’s explore.

The Human Story Behind Requirements

Before any line of code is written, great software lives — in people’s minds first.

Requirements are not just a checklist. They are stories of how people work: the decisions they make, the interruptions they tolerate, the information they need and when. These stories shape what your software must do.

According to research, the quality of requirements engineering is one of the strongest predictors of software project success, and failure to properly elicit and manage requirements significantly increases risk.

In modern development practice, constructs like user stories exemplify this shift. Agile user stories turn abstract requirements into brief narratives that spark discussion, not documentation for its own sake. A classic user story might read:

“As a sales manager, I need to approve discounts so that my team can close deals within policy.”

That narrative helps everyone — from product owner to engineer — visualise the value and function before technology choices are ever made. These stories become the foundation for real collaboration, and they keep teams aligned long after development begins.

Why Workflows Matter Before UI or Tech

Imagine a factory line without a map of stations — every worker improvises their route. Chaos. That’s what software teams face when they start with tools instead of workflow.

Workflows — the sequence of tasks and handoffs that make work happen — are the architecture of action. Without mapping them, you risk automating inefficiencies, creating system gaps, and frustrating users.

Industry best practices highlight the importance of standards, early requirement definition, and structured workflows as foundational to scalable, reliable software development.

Modern project management discipline emphasizes this end-to-end view to ensure delivery is aligned and predictable.

When teams map workflows first, they learn things no tool can reveal:

What triggers a process
Who is responsible for each step
What exceptions exist
Where delays or rework happen

This clarity guides every subsequent choice — integration strategy, data design, UI priorities, even security constraints.

When software is designed around real workflows and validated requirements, it becomes a powerful enabler of digital transformation, helping organisations modernise operations without disrupting how work actually gets done.

The Tale of Waterfall and Agile — Different Ends, Same Core

Traditionally, the waterfall model enshrined early requirements and design as discrete phases — a structured, linear path with documentation as the roadmap. While waterfall eventually lost favour in many contexts for being too rigid, the underlying idea — understand it before you build it — remains valid.

Agile methodologies adapted this principle to be more iterative and collaborative: requirements evolve, but the work starts with shared understanding rather than tech preferences. Whether in classic waterfall or agile sprint cycles, starting with deep understanding consistently leads to better outcomes.

Ignoring workflow or requirements doesn’t make development faster — it just defers inevitable pain.

The Narrative of Good Software Engineering in 2026

Today’s custom software development is far richer and more nuanced than in decades past. Teams are distributed, systems are interconnected, and expectations are high.

Great teams tell software stories that matter — narratives of user needs, business value, and capability priorities.

They ask questions like:

“What’s the real event that triggers this workflow?”
“What exceptions do people encounter that we must support?”
“How will users actually interact with this feature?”

These are not checkboxes — they are conversations. In requirements elicitation practice, effective engagements often include interviews, workshops, observation, and prototyping to surface hidden needs and latent requirements that surface only when stakeholders tell their stories.

The Cost of Too Many Tools and Not Enough Insight

Tools have their place. They enable collaboration, automate testing, and accelerate delivery. In fact, modern development toolsets — from version control and CI/CD pipelines to real-time collaboration platforms — support workflow and quality when the underlying requirements are solid.

But when tools precede understanding:

Teams spend time integrating things that don’t matter
Interfaces please executives but frustrate users
Projects accelerate toward features, not value

And what remains at the end? A codebase that is efficient, modern, and unusable.

How Leaders Write Better Software Stories

As a partner advising software delivery teams, here’s the mindset that separates predictable outcomes from costly surprises:

1. Start with People and Workflows

To paraphrase a timeless engineering insight:

measure twice, cut once.

Map workflows with stakeholders before making tech bets.

2. Use Requirements as a Conversation Tool

Write user stories — not documents — to capture functional expectations in a way that sparks discussion and alignment.

3. Think in Scenarios Before Screens

Use cases and scenario modelling help teams see what the system should do under real conditions, not just what it looks like.

4. Let Workflow Guide Tool Selection

Only after workflows and requirements are clear should you evaluate which frameworks, IDEs, or platforms best support your goals. Tools are amplifiers, not directors.

Conclusion: Software is a Story First

In 2026, custom software engineering is as much about narrative and clarity as it is about code. The projects that succeed are those where teams took the time to understand

What the business actually does
What users truly need
How workflows unfold in reality

— long before picking tools or polishing screens.

Software that represents real work — not assumptions — is the kind of software that delivers reliable outcomes, sustainable value, and happier users.

And that storytelling mindset? That’s the true foundation of success.

Custom Software vs Commercial Software

iExcel Custom Software Programmer working in a software developing company office

As a growing number of daily tasks and complex enterprise processes require automation, organizations are confronted with the sometimes daunting task of finding the right digital solution within a wide variety of digital transformation options available on the market.

In order to understand how Custom Software and Commercial Software differ, we first ought to provide a definition for each of them:

A Commercial Software is a piece of software that was designed and developed for the purpose of sale through licensing to an end-user or for commercial purpose.

A Custom Software is a piece of software that is especially developed for an organization according to their specific requirements.

Now that we have defined Custom and Commercial Software, we can look at a number of examples. Microsoft Office and Google Apps are good examples of Commercial Software. Indeed, many users buy those commercially available software products off the shelve in order to produce documents, spreadsheets and presentations.

A customer relations management system that fits the needs of a successful commercial activity or an online medical patient interface that supports the activity of a clinic are examples of custom software development.

A software can be evaluated according to 5 key dimensions:

Efficiency
Cost
Time
Maintenance
Security

We are going to develop each of them:

Efficiency

The efficiency of a software is measured in the amount of support for the operation, and increase in productivity it will generate.

Commercial software are built as a finished product to be sold in large quantity to a target market. The companies behind those software use heavy marketing to promote their brands and to get the software known. As they become widely accepted by the industry, they tend to follow standards. It is also likely that current and future staff are already familiar with the software. This provides an advantage in terms of user software acceptance, and ability to work with the software. In addition, as many people use the same software the software name is familiar to many, which gives a feeling of reassurance when buying it. Also, the many user base plays in favour of debugging as more bugs are being detected and corrected. On the other hand, commercial software can be heavy to run due to the complexity of their features. They tend to get over-complicated as they cater to a wide range of users within an industry with various business models or across industries, and there is a concern to be sure all items of all businesses ever using the software are included. At the same time, they can become very limitative since they are designed as a finished product rather than an on-going process. As a result, it is many times the business model that needs to adapt to the software rather than the software that is designed to support an existing and successful business activity.

Successful business models usually are unique in a number of ways. A commercial software will not be adaptable or even exist for it. Custom software are designed together with the end-user, after a thorough analysis of the needs. This offers two advantages. First the software is tailor-made for the need of the business, without the unused features present in commercial software; which results in a lean, and easily approachable interface. Second, the research and analysis steps are a good introspection opportunity for the teams. It allows them to discuss, review and potentially improve some of their business processes at the time the software company is creating new structures to support them. Custom software allow for increased efficiency and to achieve business goals faster as it is adapted to a specific business without limitations, and it is highly scalable. Custom software provide an organization with the set of tools it needs.

While standardization is crucial when selling a car or a handbag where the product needs to be identical in its essence every time, when it comes to support a business with many unique features, innovations and a fast growing pace, customization of the supporting tools is vital. It is nevertheless important to note that a custom software should be developed by a reputable company with track record, that have a high degree of listening and understanding of business processes. A software company that has the ability to transform business needs and ideas into workable, efficient and user-friendly software products.

Cost

Commercial software tend to have lower upfront costs. Since the cost of development is spread amongst a large number of users, it makes more sense for those software companies to offer an attractive entry price. That said, an organization should be aware of how the many upgrades, service fees, yearly maintenance fees, and installation fees add up in the long run. Cost of customization, when possible, also comes at a higher price tag.

Commercial software often provide free trials, which is a good way for the user to evaluate the software. That said, this process will make the user go through the implementation and data migration process. This can often create a bias when choosing the right software in the way that it creates an early switching cost. Indeed, as users have accomplished a considerable amount of work with the trial version, and the data has already been transferred there, settling for the current software often appears as an easier option than restarting the process all over again.

As a finished product a commercial software will partly work for your company as it is now within the size and parameters of a given time. As businesses grow and change, so do their support and automation needs. As commercial software do not really adjust, the business must adjust to the software. As a result, slowing productivity, and missing functionalities can become quite costly. More often than not organizations purchase a piece of commercial software only to discover that it does not work for them.

Custom software carry higher upfront costs, which can sometimes deter organizations from taking a step into that direction. When going for the custom software option an organization must see it as an investment into efficiency, higher productivity and reduced costs in the long run. There is no doubt the higher upfront costs alleviate over time, making the custom software option the less costly of both options. As custom software are built using well-known technologies, first there is not a risk of getting stuck because a development company ceased its activity or decided to discontinue a product; a custom software can always be upgraded and amended. Second, the end-user is free to carry the software product to another developer. Those two reasons alone ensure that there are very little to no switching costs but also a wider range of choices for affordable, enhancement development, support and maintenance.

Time

Commercial software are more or less ready to use when bought as they are designed as a finished product. For an organization that cannot afford to wait, this present a clear advantage, even if time gained at the beginning can turn out to become very time consuming in the long run as the needs of an organization evolves and the commercial software is unable to cope with the new business requirements.

While it takes time to build a custom software, the resulting software product is often leaner and adapted to the organization’s needs. The research, design and conceptualization undertaken by the software development company together with the organization is an exercise that usually provokes a good introspection on all the processes and structure of the company. It offers the opportunity to re-examine, and enhance the way things are done, which in turns makes the organization more productive and profitable. The time it takes can also be seen as an advantage as the organization will be able to see the project as it is being built, which means that the collaboration between the developer and the organization lead to a better scoping, scheduling and development of the software, which can then be tested and tweaked as per the organization’s needs.

Maintenance

Commercial software sold by serious companies often come with serious and steady support. While customization is sometimes possible it usually comes at a very high price. Sometimes the programming language is bespoke or only know by few developers, which makes maintenance difficult and costly. Bespoke technologies also present a considerable issue when it comes to integration. An organization will be required to use a range of software to conduct their operations. With commercial software, it is unlikely that those various software products integrate and talk with each other. For example an organization’s eCommerce site might not work with the features available in the commercial software.

Good software company will use repositories, documentation, widely used frameworks and technologies. This will ensure that the software is maintainable by the developing company but also by any other or the organization’s internal IT team if required. New platforms, software, modules can be developed, enhanced and integrated with the existing software.

Security

Commercial software are delivered with security features that are standard at the time they are sold. There is very little evolution in commercial software. They are designed as finished products, and might have been around for a while. They sell as long as they have not expired their commercial life cycle. As a result many are built relying on older technologies that are more prone to attacks. Their popularity also presents a security disadvantage. Indeed as many companies use the same software, it is easy for a competitor to understand an organization’s processes and limitations based on the knowledge of the commercial software in use. It also makes the organization more vulnerable to cyber-attacks, as hackers would know the structure and security features of that commercial software, and where to find what they are looking for. As it is used by many companies, hackers do not need to learn a new software, which makes a commercial software a prime target.

Last but not least, organizations using commercial software are dependent on the software provider. The organization is directly affected by changing terms and conditions, new pricing, and state of their business. If the software provider decides to discontinue the product, the organization is left with no choice but to change to a new software.

Custom software use latest technologies. Customization also means that an organization can set up access rights as they like, which offer better control over the organization’s data security. Due to the uniqueness of a custom software, it is difficult for cybercriminals to attack a custom software, it has specific security features that protects the data. As there is no comparable software in the market, cybercriminals have no means to study those security features.

Overall, organizations need to evaluate their options according to their needs and goals based on the dimensions explained above, and make an informed choice. Commercial software can be the recommended option for a certain type of tasks, when time or money does not allow for another option. Some organizations may even learn a business from using and following the structure of a standard software. However, if an organization’s business model is well defined there are many reasons including efficiency, security, longevity, cost and adaptability that strongly suggest that a custom software will ensure better return for longer.

Smart Data Treatment Leads to Better Decision Making

Tyco Water Asia, part of US Fortune 500 company Tyco International, and a leading supplier of systems for the water industry, faced a challenge. As it considered whether to invest in a large scale, multi-million dollar development project, it needed to understand whether the project would meet its customers’ future needs.

However, says Ian Jacob, Tyco’s Managing Director, collecting the data necessary to make a decision was not straightforward. “We simply couldn’t get the detailed data we needed – it’s just not available,” he says. “We could have commissioned a company to go and get it, but that probably wasn’t the best solution for us because it needed to be very targeted.”

“I didn’t really understand that you could actually do what they did in Excel. I didn’t know it was possible.”

Ian Jacob, Managing Director, Tyco Water Asia

So, he says, the Tyco team decided to develop its own survey. By carrying out the survey in-house, and having his team collect data from customers directly, Jacob believed that Tyco would benefit from a more targeted approach.

But even then, he knew the survey’s design would be critical to its success. “I was concerned about the outcome, because we could have had a whole lot of sales people out collecting data, and if they didn’t get the content right, the answers would be meaningless,” he says. To avoid this, realized Jacob, “it was really important to have a standardized questionnaire.”

As he considered the best approach, Jacob had a conversation with Jeremy Artan, Managing Director of iExcel Consulting, about Tyco’s plans. Until then, he says, he did not know about the functionality a tailored Excel solution could provide. “I knew Jeremy and I knew he had some skills in that area,” remembers Jacob. “But until he started to explain to me what they could do, I didn’t really understand that you couldactually do what they did in Excel. I didn’t know it was possible.”

Artan agrees that Excel’s capabilities are more impressive than most businesses realize. “Excel has developed into a robust application, capable of handling several users and external data sources,” he says. “Yet it is still fully flexible. Too often, companies are stuck with big off-the-shelf software that only partly works for them. Excel software has no limits and continues to evolve as a company grows.”

The Tyco team had started work on a standard series of questions for its sales team to work through with customers. But there were still risks: the data gathering exercise might lack the professional image provided by an outside company; the data could suffer from bias if collected by customer-facing sales teams; the project would use up valuable time and resources; and the final data would have limited reporting features.

Most importantly, says Jacob, if the data was not accurate enough, Tyco risked making the wrong investment decision. So, impressed with Artan’s approach, Jacob appointed iExcel to develop a tailored Excel-based questionnaire. Tyco provided iExcel with its list of survey questions, and asked it to design an efficient Excel-based platform to help move customers quickly through the survey.

Tyco specified that the questionnaire should look professional and be easy to navigate; questions should be mandatory and appear automatically based on previous answers; and all the data should be collected in a single database to provide flexibility when assessing the results.

Even then, says Jacob, used to working with regional suppliers who often had to revisit projects several times before their solutions met Tyco’s needs, “I didn’t know what sort of outcome we would get from iExcel.”

But he found the process pleasantly straightforward. “I gave them an indication of what we were looking for; we gave them the data; and then they came back with the solution and it was already 99% done,” he says. “They delivered us that solution very quickly, and there was virtually no tweaking in it. We changed some questions, but other than that it was great.”

“The solution was outstanding. The dashboard that we got – we’ll be using that for the next three or four years on this project.”

Not only did the platform iExcel designed do exactly what it was meant to, says Jacob, but it will continue to be useful for Tyco beyond the survey for which it was built. “The solution was outstanding,” he says. “The dashboard that we got – we’ll be using that for the next three or four years on this project.”

iExcel’s dashboard has been particularly effective, he believes, because of the depth of data it can provide. “It allows us to keep going back and looking in a very efficient way at what the data was and how it applied,” he says. “Their solution allows us to drill down into the data and see specifically who it came from. We can analyze it by region; by customer; by customer type – all of those things. So, it’s a very, very efficient way of analyzing a lot of data.”

Another advantage of working with iExcel, believes Jacob, was the commercial approach the team brought to the project. “The main benefit was their ability to understand what we wanted and then deliver it,” he says. “They have a pretty good commercial sense of what needs to be done, and an ability to grasp our requirements. I just think we got an output that we could not have got from another local company.”

iExcel’s Artan is proud of his team’s commercial attitude. “Most of our employees have grown their skills through roles as analysts or strategists,” he says. “This provides them with a business understanding and business approach that most IT people lack. As a result, our solutions not only work, but they fully integrate within our client’s business.”

The dashboard that iExcel produced for Tyco, reflects Jacob, “did exactly what we wanted.” And, impressed by the project, he expects Tyco to work with iExcel again in the near future. “We’ve shown it to other people within the business,” he says, “and some of them want to do similar things. Like me, they also didn’t understand that you could actually do this in Excel.”[/vc_column_text][/vc_column][/vc_row]