The UK Government announced the AI Opportunities Action Plan to accelerate the development of AI technologies and support businesses in adopting AI responsibly.
The plan includes creating ‘AI Growth Zones’ across the UK to facilitate the construction of data centers and expanding the AI Research Resource (AIRR) to foster AI-driven growth across industries such as finance, healthcare, and manufacturing.
Over the next six months, the government will develop a long-term strategy to support AI infrastructure, backed by investments in software, skills, and computing capabilities over ten years.
However, for businesses to take full advantage, they must first ensure they have the right foundations in place. And that starts with optimizing processes and tackling SaaS sprawl. Without clean processes and a streamlined tech stack, AI adoption will be inefficient and ineffective.
Chief Product Officer and Chief Technology Officer at Nintex.
The perils of SaaS sprawl
SaaS sprawl happens when companies adopt multiple digital tools to meet business needs, often leading to redundant app functions, inconsistent workflows, and siloed data. As a result, business processes are defined around the rigid workflows within SaaS applications instead of mature processes defining the software footprint. Businesses use countless apps nowadays, meaning IT teams struggle to maintain visibility over their entire software ecosystem. Research shows that business departments control 70% of SaaS spending and more than half of their applications, while IT manages less than 20% of third-party software.
This fragmentation weakens AI’s ability to drive impact holistically, including limited visibility into data and limited context of the processes within an organization.
Excessive SaaS usage and ‘duct taped’ processes also create inefficiencies in workforce productivity. Employees often waste time toggling between different applications, manually transferring data, and resolving discrepancies between systems. This not only slows down business operations but increases the risk of human error, further compromising AI’s effectiveness.
Reducing SaaS sprawl is not just about cutting costs – it’s about creating an interconnected system where data, context, and process logic are orchestrated efficiently, helping ensure that AI can generate high-quality impact. Pivoting to a process first framework, companies can define what good looks like and create a digital experience that fits the process they need leading to tech stack consolidation, unified workflows, enhanced data integrity and ultimately optimal AI performance.
Three steps for strong AI foundations
Step 1: Identify and map business processes
Far too often, businesses buy software to address processes, but there’s no amount of technology that can fix bad processes. Instead, businesses should address process first and build custom solutions that operate based on their systems, approval flows, data, and business logic. Companies can use process management tools to identify and map the business processes they want to run across their teams. As part of this process, businesses can uncover redundant technology, broken integrations, and create a plan to consolidate applications to make critical solutions work together more efficiently. This approach eliminates inefficiencies, reduces manual intervention, and enhances AI-driven automation. IT teams can regain oversight and governance to ensure compliance, while also creating standardized workflows that maximizes the value of existing software.
Step 2: Automate processes and build applications
Once businesses have identified and mapped their processes, the next step is implementing automation to streamline and orchestrate them. Automation tools and workflow management systems help eliminate repetitive manual tasks while ensuring consistency and accuracy. From the streamlined workflows to automated document generation and forms, businesses can align automation with their processes and leverage low code and AI to build custom solutions that create a seamless, scalable system that offers that all-important operational efficiency.
While SaaS sprawl is a huge problem for businesses, the solution isn’t to scrap SaaS altogether. Rather, it’s about removing the need for supporting software around core business systems that incurs costs and damages efficiency. Custom apps can help businesses achieve a happy equilibrium. They eliminate the need for ancillary software solutions by leveraging automated workflow data and low-code development to build purpose-built solutions for their operations.
Step 3: Infuse AI for scale
Once custom solutions are built around unique workflows and business logic, businesses can begin to infuse AI where non-deterministic capabilities are needed to scale. AI is a powerful adaption to traditional, deterministic automation because it can:
• Analyze unstructured data (like text, images, or voice)
• Learn patterns from past data
• Make probabilistic predictions or classifications
• Adapt over time as new data becomes available
From customer support triage to fraud detection, AI can be infused into custom apps to help streamline processes and navigate inputs based on probabilities, context, or learned patterns.
Winning the AI race
Industry experts, like Forrester, agree that building custom apps that are infused with AI is the future instead of buying multiple off-the-shelf SaaS tools. By integrating AI-driven automation into custom applications, businesses can not only reduce software sprawl but unlock new levels of efficiency, agility, and innovation.
However, to maximize ROI with AI, it must be applied to the right opportunities with the right foundations in place. This means efficient business processes must be mapped out and automated across all the systems of record, data must be harmonized to provide proper context, and AI must be leveraged for the non-deterministic nodes where traditional automation can’t drive efficiency.
By combining process, automation, and custom applications, businesses create a scalable, intelligent tech stack that adapts and improves over time – eliminating inefficiencies and unlocking new levels of productivity. When thinking about winning the AI race, businesses should keep in mind that no number of systems can fix bad processes. Creating a strong foundation rooted in optimized processes will help ensure they take full advantage of AI.
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