Rethinking Automation: Why Businesses Need A Long-Term AI Strategy

Enterprises hoping for a quick AI fix may be disappointed, as true transformation requires a long-term vision. A successful AI implementation that will make a meaningful impact across the business hinges on a considered strategy rooted in long-term goals and a thorough understanding of existing processes.

We look at some of the ways enterprises can embrace a phased, analytical process to pilot AI where it can make an immediate impact, while laying the groundwork for ongoing improvements.

One of the biggest mistakes organisations make when deploying AI is jumping in too quickly without proper planning. A global survey ABBYY ran last year revealed that the top reasons stated by business leaders for the failure of AI projects were ‘vague goals’ (43%) and being ‘too hasty’ in deployment (21%).

Business leaders should not embark on the AI transformation process without pinpointing exactly what they want to achieve, what needs to be changed, and how they are going to go about it. The first step should always be fully assessing current processes and workflows to identify the bottlenecks and overly time-consuming tasks before making any decisions.

The key is in the planning, establishing a decision-making process that is driven by data, through analytics tools that can gather insights and inform strategic decisions – i.e., Process AI.

Process AI uses a combination of tools and techniques, including process intelligence and machine learning, to analyse, automate, predict, and monitor processes across your organisation. It can interpret time-series data and logs from your business systems to identify automation opportunities, analyse process performance, and predict where bottlenecks may arise.

Process AI platforms that integrate task management and process mining tools can create a real-time digital twin of your operations, revealing where AI can deliver meaningful impact. With this analytical approach, businesses gain clearer insight into where to deploy new solutions and resources, paving the way for more effective and targeted AI implementation.

Once the bottlenecks are identified through Process AI, the next step is injecting Document AI into processes.

About 90% of business processes contain documents —whether that’s accounts payable, contract management, or compliance reporting. Automating these processes is your key to unlocking limitless business efficiencies, alleviating staff who are drowning in paperwork.

Document AI can reduce invoice processing times by as much as 90%, as demonstrated by METRO AG, an international wholesale company with 17 million customers in 30+ countries within the hotel, restaurant, and catering industry.

Using ABBYY’s Document AI, the company was able to streamline and speed invoice processing from one to two days to just one hour, thereby increasing productivity, enabling more clients to take advantage of customer benefits, and accelerating revenue for the company.

In today’s rush to adopt AI, businesses can find one-size-fits-all solutions for a range of different tasks tempting. Yet these generic AI approaches often miss the mark, overlooking a business’s unique needs and exposing organisations to risks.

To truly stand out and gain a competitive edge, organisations require a tailored solution. Purpose-built AI delivers precision, speed, and specialisation to drive real transformation for businesses.

Designed with a sharp focus on specific tasks or industries, purpose-built AI models grasp the intricacies of their fields to produce outcomes that are not just relevant, but also highly accurate. By zeroing in on the unique needs of an organisation, purpose-built AI can drive meaningful transformation while eliminating wasted time, resources, and energy on irrelevant tasks.

Take the finance and accounting department, for example, where accuracy is critical. Document AI can process invoices, purchase orders, and other finance documents with precision, significantly minimising the risk of costly errors. And because organisations can easily customise these AI solutions, internal teams can explore, experiment, and adapt AI models for yet greater precision.

Companies can reap huge benefits by taking a data-driven and tactical approach to AI investment. Our survey noted that in terms of ROI, almost half (47%) of enterprise executives saw a 2x return on their AI investments.

Beer giant Carlsberg recently saw strong ROI by leveraging Document AI to automate data capture from incoming orders, achieving a touchless order processing rate of 92% and saving over 140 hours of manual employee data entry per month. This drastically accelerated customer deliveries, subsequently improving customer satisfaction and loyalty.

Meanwhile, one of the UK’s largest pastry manufacturers  saw exceptional ROI by using AI to automate data extraction from complex transportation and logistics documents – reducing their customs clearance times at the EU/UK border from one hour to just five minutes.

Many businesses are still in the short-term automation phases, but strategic direction is key to sustainable, strategic AI adoption.

Using automation as a foundation for innovation allows businesses to align AI investments with goals and manage the risks. A long-term AI strategy isn’t just about keeping up with trends, it’s about building useful, functional systems that evolve with your business.

ABBYY recently launched new Process AI solutions designed to accelerate consulting projects and deliver advanced analytics for document-centric workflows. These innovations, help enterprises unlock deeper insights from business content and make smarter decisions faster.