Learn how to determine if Artificial Intelligence (AI) and Intelligent Automation are the right fit for your organisation

Intelligent Automation is an extremely powerful way to boost your business’s efficiency, enhance customer experience, and secure your long-term digital transformation goals. However, this transformative power is only realised when these technologies are deployed correctly. As a strategic technology leader, it is vital to have the right strategies in place to ensure a successful implementation from the very beginning.

Implementing AI and Intelligent Automation can be akin to layering advanced cognitive capabilities onto your existing processes and legacy applications. Once these intelligent workflows are active, you must carefully consider change control for both the automated processes and the underlying applications they interact with. When thinking about intelligent automation at scale, you should view it as a major, transformative IT change programme.

Get your digital transformation off on the right foot. We have compiled a list of key considerations and challenges you need to keep in mind when determining if AI and Intelligent Automation are right for your organisation:

Control and governance

A lack of control and governance is particularly prevalent when individual departments adopt third-party AI tools or build their own automated workflows without central IT oversight. Similar to the unmanaged spread of legacy macros, shadow AI can be very powerful in the right hands, but it introduces significant operational and security risks.

Consideration must be given to who will be building and managing your intelligent processes. Strategic leaders need to establish robust governance frameworks that allow for innovation while protecting the enterprise. Partnering with expert consultants can help you implement a secure, scalable infrastructure that gives your business units the agility they need without compromising on compliance or data security.

Don’t just accept your existing processes

Intelligent Automation presents the perfect opportunity to fundamentally enhance and improve your operational workflows. You should consider if simply automating the status quo is genuinely the right solution, or if alternative cognitive improvements would lead to a better overall scenario.

Rather than just speeding up an inefficient task, AI allows you to rethink how value is delivered to the end user. Re-analyse and deeply de-compose your processes so you thoroughly understand how they can be optimised. By applying machine learning and natural language processing, you can create bespoke solutions that not only cut costs but actively improve the customer experience.

Cultural and organisational change

Adopting AI is as much a cultural change as it is a technological one. Business users, especially the end-users who will be working alongside intelligent systems, need to be comfortable and accepting that these tools are here to empower them, not replace their jobs.

At Ten10, we understand that AI is not about replacing people; it’s about complementing them. Speak with your staff regularly, provide the bespoke technical training needed, and reinforce the benefits of automation to the people who will be using it every day. Addressing these cultural shifts head-on is a proven strategy for improving talent retention. When you remove tedious manual tasks from your team’s workload, you allow your diverse technology talent to focus on high-value, strategic problem-solving.

Balance expectation and enthusiasm with realistic ROI

Realistic expectations must be set from day one. Experience tells us that no client requirement is the same, so it’s critical to ask all the right questions and cut through the hype. Like any strategic digital transformation initiative, an investment needs to be made upfront, and implementation may feel deliberate at first.

The first processes you choose to automate should ideally offer high visibility but carry lower operational risk. Jumping straight into your most complex, mission-critical processes out of the gate is a recipe for a stalled project. By adopting a pragmatic approach, you can deliver cost-effective solutions that demonstrate tangible ROI early on. This builds confidence across the executive board and secures the buy-in necessary for long-term scalability.

Creation of an entirely new capability and support function

Intelligent Automation at scale requires the creation of an entirely new capability and support function within your IT department. Unlike rules-based systems, AI models can experience data drift or encounter highly nuanced edge cases. Therefore, robust exception handling needs to be built into all processes.

Exception handling is a critical component that stakeholders often forget when they only consider the “happy path.” You must clearly establish who owns the automated process post-implementation: the business unit or IT. Creating a dedicated centre of excellence ensures that your scalable infrastructure remains healthy, updated, and aligned with your broader strategic objectives.

Develop a data strategy

Intelligent Automation constantly requires AI models to process and handle vast amounts of data, which often includes highly confidential information. This must be handled with the highest level of sensitivity and security.

You cannot rely on the easiest routes, such as unstructured Excel files and standard emails, when training AI or executing automated tasks. Governance, strict data privacy protocols, and the ability to thoroughly audit intelligent processes are essential. Ensuring your data sets are clean, diverse, and well-managed is the foundation of any successful AI initiative. When building your platform, you must prioritise a data strategy that actively prevents bias and guarantees regulatory compliance.

It’s not just about the tools

The lack of suitable documentation for existing manual processes can present a massive challenge for any automation initiative. Does everyone in your department perform a specific workflow in the exact same way? Are there underlying flaws that need to be resolved prior to introducing machine learning?

Technology is developing so quickly that it’s hard to ensure your teams evolve and adopt the skills they need to manage these new systems. Quality AI engineers and automation architects can be expensive and difficult to retain. Our Tech Academy provides high-calibre, diverse technology talent, selected and developed to provide the best combination of aptitude, relevance, and cultural fit. By utilising our Recruit-Train-Deploy model, we enable our clients to address their immediate and future tech talent needs seamlessly.

Intelligent Automation evaluation

To fully release the strategic value of an effective AI implementation, it is vital to have a robust evaluation framework in place. The careful analysis of a potential automated workflow is just as important as the algorithmic code itself. You can read our recommended process for evaluating automation opportunities below:

Our recommended IA evaluation process

A simplified evaluation process ultimately involves identifying an initial list of automation candidates that possess high business value. By documenting the exact steps and challenge areas of each process, you can establish the complexity and potential business benefit. Once this priority is known, you can select the AI toolset most suited to your bespoke needs and confidently start your Proof of Concept.

In a business landscape where error, delay, and confusion are simply unacceptable, organisations must strive for quick, accurate, and efficient processes to achieve their goals. However, relying solely on your human workforce is no longer sufficient to maintain a competitive edge. Strategic technology investment is key.

Intelligent Automation (IA), powered by Artificial Intelligence (AI), is a transformative approach that handles complex, data-driven tasks, empowering businesses to enhance efficiency, minimise errors, and concentrate on strategic endeavours. The real challenge, however, lies in its implementation. Without being fully embedded in an organisation’s digital ecosystem or a true understanding of its strengths, any automation project is at risk.

The evolution of automation

Nearly all automation vendors are now incorporating sophisticated AI layers into their software, significantly enhancing their capabilities. This evolution from rules-based automation to intelligent systems offers a practical introduction to applied AI.

This integration not only improves the efficiency and effectiveness of automated processes but also provides a seamless entry point for organisations looking to leverage AI more broadly in their operations.

As a result, strategic leaders can implement more intelligent, adaptable, and powerful solutions that bridge the gap between traditional automation and advanced AI-driven processes.

Utilising AI and IA to increase revenue and optimise processes

Implementing AI-driven Intelligent Automation effectively is key to achieving optimised processes that lead to increased revenue, efficiency savings, and an excellent customer experience. Here are some examples:

#1: Sales and transaction automation

Sales are pivotal for revenue generation, and Intelligent Automation can revolutionise your sales operations. AI-powered systems can handle complex tasks such as updating CRM data from unstructured sources like emails, preparing invoices, and applying dynamic pricing or discount codes based on real-time data. This streamlining of sales processes not only enhances the customer experience but also unlocks significant revenue potential.

A multinational company faced challenges in processing thousands of invoices manually, which led to delays and costly errors. To streamline the process, they implemented an AI-driven invoice processing solution integrated with their SAP ERP. This solution automated data extraction, invoice classification, and approval workflows. It seamlessly updated financial records and triggered payments upon approval. The addition of real-time reporting and analytics provided insights for continuous improvement, resulting in increased efficiency, accuracy, and cost savings.

#2: Customer interaction enhancement

An exceptional customer experience drives revenue growth, and AI-powered automation can elevate your customer service. By integrating Intelligent Automation with your CRM, you can handle tasks like record updating, sentiment analysis of customer feedback, and intelligent ticket distribution to the most appropriate agent. Leveraging AI-powered chatbots and virtual assistants provides immediate, 24/7 assistance, significantly enhancing customer satisfaction.

AI-powered chatbots are a great example of this. When a customer lands on your website, they can be greeted by a sophisticated chatbot. This system uses natural language processing (NLP) to understand the customer’s query and provide instant, accurate responses. For common inquiries like checking order status or product specifications, the chatbot can quickly provide information, enhancing convenience and reducing customer wait times.

#3: Data manipulation and management

Efficient data processing is crucial for streamlined operations, and Intelligent Automation ensures both accuracy and efficiency. You can automate data sorting, processing from various formats, and reporting, which reduces errors and enhances business insights. This eliminates manual data manipulation tasks that are prone to errors, ensuring data integrity and security across your organisation.

In the dynamic landscape of retail, a large chain receives diverse sales reports daily from its stores in formats like Excel spreadsheets, PDFs, and text files. Manual consolidation of this data was cumbersome and error-prone. By embracing AI-driven automation, the company transformed its data extraction and consolidation processes. Intelligent systems were tailored to retrieve sales reports from email attachments, adeptly extracting pertinent details like sales figures and product categories, before standardising the data into a unified format. This automated data manipulation not only streamlines operations but also empowers the company to make informed, data-driven decisions swiftly.

The strategic value of Intelligent Automation

When fully utilised, Intelligent Automation offers diverse benefits that align with the strategic goals of a modern CIO:

• Accessing legacy systems: IA can interact with older systems that lack modern APIs, simplifying the retrieval and management of information stored in legacy architecture.
• Collaboration enhancement: It seamlessly blends with existing resources and workflows, augmenting the capabilities of your human teams.
• Labour-intensive task automation: It reduces organisational dependency on manual processes, especially for managing peak periods such as year-end or regulatory filing dates.
• Operational cost control: It minimises expenses by optimising workforce allocation and improving process efficiency.
• Accurate data handling: AI-powered systems process vast data sets with precision, extracting insights from both structured and unstructured information.
• Improved customer experience: It enables the delivery of prompt, customised services at scale.
• Insight generation: It utilises AI and machine learning to derive valuable, predictive insights from your operational data.

Recent trends highlight the growing significance of these technologies for strategic leaders:

• Increasing investments: A PwC survey reported that 37% of companies have already implemented AI in some form, and 84% plan to invest in AI within the next three years.
• Projected growth: The RPA market is projected to grow from $22 billion in 2025 to $30.85 billion by 2030, with a CAGR of 39.9% from 2023 to 2030. This growth is driven by efficiency improvements, cost reductions, and advancements in AI and cloud technologies across various industries such as BFSI, healthcare, retail, and manufacturing​.
• Strategic advantage: Over 900+ job types in the US contain some tasks that could be assisted by technology.

Hear what it takes to lead through the AI revolution

For many businesses, AI is no longer an experiment; it’s an essential part of competitive survival and growth. But the path from pilot project to fully integrated, value-generating enterprise AI is fraught with challenges. Senior leaders face three hurdles:

• Developing a coherent AI strategy
• Navigating the expanding landscape of risk and regulation
• Executing real-world operational integration without disrupting core business functions

In this webinar, we’re moving beyond the hype to provide practical solutions to the strategic challenges of AI adoption. We cover the essential frameworks and considerations necessary to lead your organisation through the AI revolution.

What you will learn

• Strategic Imperatives: Translating AI’s potential into a robust business strategy that drives tangible ROI
• Operational Friction: Identifying and mitigating the core process and cultural barriers to widespread AI adoption
• The Governance Gap: Addressing critical governance issues, including data security, ethical AI, and ensuring compliance in a rapidly evolving regulatory environment

Do you know if your patients’ insurance and credit card details are up to date before a clinic begins? Are you frustrated with manual processes slowing down clinic bookings and resource allocation? Are you tired of chasing patients for their appointments while trying to maintain a high-quality patient experience?

These operational bottlenecks are ideal use cases for Artificial Intelligence (AI) and Intelligent Automation. Implementing these transformative technologies saves valuable time and budget, ensures prompt billing, and meets strict regulatory requirements. For strategic IT leaders, embracing bespoke AI solutions is a critical step in a broader digital transformation journey. Here is our overview of how AI and Intelligent Automation can benefit and empower organisations in the health industry.

Why should AI be used in finance?

In the world of finance, even small errors can cause significant results. You need only look to Santandar, which paid out £130 million on Christmas Day 2021 in error due to a scheduling issue that resulted in roughly 75,000 accounts being paid a second time from the bank’s own reserves.

Intelligent Automation (IA), powered by Artificial Intelligence (AI), offers a powerful asset for handling complex, data-driven tasks, making it perfectly suited for the financial industry. It’s estimated that there are over 1 billion purchase transactions around the world every day, all relying on technology infrastructure to do two essential tasks – transfer money and, most importantly, do it quickly. How, then, can AI help financial institutions?

Use #1: Achieve growth without compromising older systems

Financial companies are often long-established and have made many changes in their systems over time. In some cases, these systems have become monolithic and are essential to the mission-critical operations of the organisation. Downtime of these systems, either planned or unplanned, risks consumer irritation and can detrimentally impact confidence in an institutional brand. Due to the often global customer base that relies on these systems, financial companies can feel torn between growing their capabilities and putting older code at risk. This has given rise to leaner, challenger banks who have dominated consumer score tables in recent years.

Intelligent Automation provides a strategic solution for introducing the benefits of a modernisation programme while maintaining the core systems and architecture that the organisation runs on. Where legacy systems lack modern APIs or clean back-end processes, AI-driven solutions can interact with the front end of existing internal systems, mimicking human actions to execute complex tasks. This allows an organisation to achieve performance indicators previously thought to be years away in a fraction of the time. It also provides IT teams with the necessary breathing room to continue with long-term modernisation, but with reduced risk and time-sensitive pressures.

Use #2: Maintain regulatory compliance

Another byproduct of the size of many financial companies is the volume of regulations and guidelines they must remain compliant with to continue operating in their many international markets. Compliance is a notoriously laborious task, though essential to business operations. It requires analysis free of bias, making it a prime candidate for AI and Intelligent Automation.

AI models can be trained to understand regulatory documents, identify changes, and assess their impact on internal processes. Advanced logging can be applied to any automated process to confirm with, or expand on, the required audit trail. This can be achieved by introducing business-readable checkpoints through emails, scheduled reports, or long-term activity logs, which can be made accessible at any time should an audit be required. AI systems will not deviate from their programmed logic, nor will they make mistakes, assuming they have been developed to a high quality. As such, you can be confident that your intelligent systems are diligently working to ensure processes remain accurate, compliant, and auditable within specified timeframes.

Use #3: Increased efficiency

Intelligent Automation is an exceptional tool for removing inefficiencies in people’s workflows. This can have a massive impact in the world of finance as companies regularly have many departments and carry large headcounts. By automating data-intensive and repetitive processes, AI frees up human intellect for more strategic work.

Utilising this technology, regular tasks such as running audits, analysing transaction patterns for fraud, and generating system reports can be carried out by an intelligent system, overseen by a small number of human supervisors. Staff time can therefore be redeployed away from inefficient workflows. This means everyone from senior staff to more junior team members can focus on higher-value tasks where human insight, creativity, and empathy are required.

Use #4: Burst capability

A significant advantage of investing in an intelligent, automated workforce is the comparatively low cost for each hour of productivity. For example, an intelligent automation licence can operate 24/7, delivering substantial value for a predictable cost.

A properly configured intelligent automation platform would not be restricted to any specific task or function. Instead, AI-powered systems can operate across an organisation, focusing on tasks according to a multitude of specified business logic such as job priority, SLA, or completion time targets. This allows the organisation to automatically reallocate and scale its digital resources according to the greatest need of the business at short notice. This capability can be deployed with no additional training requirements or configuration, whilst de-prioritising tasks of lower importance until the burst in demand is over.

Use #5: Improved customer experience

Many financial companies already have two features in place to carry out the bulk of their customer service work: call centres and chatbots. However, there is great potential for AI to enhance how these two functions work.

AI can dramatically improve chatbot functionality, moving beyond simple, scripted answers to understanding customer intent and resolving complex queries. This allows customers to complete a greater number of tasks by themselves and with 24/7 access. Human supervisors are still needed for issue resolution and to complete more sophisticated tasks that cannot be completed by an automated process. However, AI can assist here too. By using natural language processing (NLP) to monitor call centre conversations in real-time, AI can provide agents with relevant information and next-best-action suggestions, speeding up tasks that require a supervisor and improving first-call resolution.

Witness the power of Agentic AI in action, revolutionising your testing with intelligent, autonomous automation

There continues to be more and more emphasis being placed on development teams to deliver faster, with fewer resources, whilst still achieving the necessary levels of quality for the business and customers. Traditional test automation can help but often it is rigid and fragile, breaking the moment application changes which often leads to high levels of frustration and ongoing maintenance.

Agentic AI has the potential to change that.

Instead of running fixed scripts, AI agents can understand intent, adapt in real time, and work together across your existing tools, from Playwright and GitHub MCP to your CI/CD pipelines. The result? End-to-end autonomous workflows that cut repetitive tasks, reduce costs, and accelerate releases.

In our webinar, originally hosted in November 2025, we showcase how Agentic AI is transforming quality engineering, moving beyond chat-based tools or single-task agents to truly connected, intelligent automation that evolves with your software.

What you will learn

• Why traditional automation falls short in modern delivery cycles
• The difference between chat tools, AI agents, and Agentic AI
• How prompts + context create production-ready automation
• Live Demo: a full test cycle, from generation to CI/CD reporting, with no manual steps
• Real-world MCP integrations already reshaping QA workflows

Client:
Ordanance Survey (OS)

Industry:
Public Sector

Technologies:
Azure Databricks, Apache Hadoop, CI/CD Pipelines, Advanced Observability Tools, Disaster Recovery Testing

Ten10 Capabilities:
Data Automation

Learn how to maximise the value of Intelligent Automation by improving opportunity generation and simplifying cost management

In the rapidly advancing landscape of Intelligent Automation (IA), two of the most pressing challenges are generating a robust pipeline of automation opportunities and managing the costs associated with support and maintenance. By addressing these areas strategically, organisations can unlock the full potential of their IA initiatives and drive significant business value.

Here’s how to tackle these challenges head-on:

Building a strong automation pipeline

The Challenge: Insufficient opportunities for automation

A thriving automation program depends on a steady flow of high-impact automation opportunities. Unfortunately, many organisations struggle to maintain this momentum, leading to underutilised resources and missed efficiency gains.

1. Infrastructure for opportunity submission

Is there a seamless way for business users to submit automation ideas? Implementing a system like JIRA or ServiceNow allows users to submit opportunities directly to the automation team. This ensures that the people closest to the processes are consistently feeding potential projects into the pipeline.

2. Effective pipeline management

How are you managing the flow of automation ideas? It’s essential to have a clear triage process, where subject matter experts review each submission, provide timely feedback, and determine whether IA is the right solution. This prevents time and resources from being wasted on unsuitable processes and ensures only viable projects make it through.

3. Metrics and optimisation

Are you tracking the right metrics to measure success? Regular monitoring is crucial to ensure your automation initiatives are delivering the expected value. Key metrics to consider include:

• Hours or Full-Time Equivalents (FTE) saved through automation
• Departmental adoption, which can foster healthy competition and drive further innovation
• Realised vs. projected benefits, especially in light of changing business landscapes like those experienced during COVID-19

4. Communication infrastructure

When bots go live, does everyone who needs to know get informed? Establishing a communication system that provides updates on both performance and potential scalability across departments is essential. Senior management often only hears about automation when something goes wrong—regular communication about successes ensures they see the full value of Intelligent Automation.

5. Showcasing Intelligent Automation capabilities

Are you actively showcasing what IA can do? Holding half-day agile sessions with business teams to demonstrate bot capabilities and outcomes not only builds excitement but also strengthens buy-in across the organisation.

6. Engaging senior stakeholders

Senior leadership engagement is critical to the success of any automation program. Rather than passively waiting for them to submit automation ideas, proactively identify high-value opportunities and give stakeholders specific objectives—such as saving a certain number of hours per year—to secure their commitment.

Managing the cost of support and maintenance

The Challenge: Rising costs of automation support

As Intelligent Automation programs scale, so too do the costs of maintaining them. Striking the right balance between launching new automation projects and managing existing ones is key to long-term success.

1. Ticketing system for issue management

Do you have a system to handle both issues efficiently? Bots can automatically generate support tickets in tools like JIRA when they encounter problems. This allows for quick resolution and long-term tracking of recurring issues, which helps identify bots in need of redesign or optimisation.

2. Selective process automation

Not every process is suited for automation. Do you have the right team in place to challenge requests for automating unsuitable processes, even if they come from senior management? A clear, criteria-driven approach ensures that only the most impactful and feasible processes are automated.

3. Scalability of IA solutions

Are your IA solutions designed for scalability? If multiple bots rely on the same system interface, ensure that changes to the interface can be addressed in one place, rather than requiring updates to each bot individually. This significantly reduces maintenance costs and system downtime.

4. Optimising licence utilisation

Are you getting the most out of your Intelligent Automation licences? Since licences are often time-based, it’s essential to optimise their use across a 24-hour cycle to reduce program costs and maximise your return on investment.

Consider whether you can reduce the number of licences in non-production environments like UAT (User Acceptance Testing). It’s common for programs to maintain licences in these environments that go underutilised, leading to unnecessary expenses. Regularly reviewing and adjusting licence allocations can significantly cut costs without impacting performance.

5. Strong governance and oversight

Effective governance is vital to ensuring long-term success. Are there coding guidelines in place, and is code regularly reviewed by senior team members? Do you have up-to-date documentation to ensure smooth bot maintenance, especially during staff transitions? These safeguards prevent future technical debt and ensure compliance across your automation program.

6. Onboarding new staff

A well-structured onboarding program is essential for getting new staff up to speed quickly and aligned with IA best practices. At Ten10, our industry-leading academy allows organisations to fast-track onboarding, providing access to the best tech talent through a two-year program that culminates in permanent hires.

Intelligent Automation is an incredibly powerful tool, but it’s important to set realistic expectations. Be clear with stakeholders about what IA can and cannot do to avoid disappointment and maintain a positive outlook on automation’s capabilities. Ensuring your team has the necessary skills for IA implementation and management is also crucial. While citizen development can be a tempting shortcut, without proper training, it often leads to inefficient automation, errors, and costly maintenance issues.

By addressing these key areas—opportunity generation, pipeline management, cost control, and skill development—organisations can harness the full potential of Intelligent Automation, driving efficiency, reducing operational costs, and delivering substantial business value.