How organisations can avoid putting their AI projects in jeopardy

By Ash Finnegan, VP GTM innovation and transformation at Conga.

  • Friday, 16th June 2023 Posted 1 year ago in by Phil Alsop

Technology is evolving constantly, providing new ways of operating and doing business. Innovations such as artificial intelligence (AI) are getting a lot of attention and moving ever closer to the centre of the enterprise as leaders recognise its benefits. According to Deloitte’s State of AI in the Enterprise1, 94 percent of business leaders agree that AI will be critical to their overall success over the next five years. However, that does not mean it is easy to implement as part of a company-wide digital change programme. The same study found that nearly half of all business leaders struggled integrating AI into their organisations’ daily operations and workflows. In fact, Deloitte found that those businesses starting new AI projects have had varying success when it comes to proving genuine business value. Although short-term technology spending is expected to increase, businesses cannot afford to keep redesigning and remodelling AI programmes. Instead, leaders should approach AI and automation far more strategically and in a phased manner – especially when it comes to scaling AI solutions across their organisation – if they want to minimise disruption or deliver a true return on investment (ROI).

Forget AI – focus on effective revenue lifecycle management

Business leaders need to reconsider how they approach digital transformation and stop implementing technology as if it is going to solve all their problems. Instead, organisations should start by clearly defining what it is that they are trying to achieve. In this case, accelerating core business processes that ultimately generate revenue. This involves reviewing all areas of the business – whether marketing, sales, legal or finance – aligning objectives, unifying systems and streamlining core processes, ensuring that they relate back to the overall business function. This is commonly referred to as revenue lifecycle management. It involves bringing cross-functional alignment and collaboration across an organisation. The goal is to bring teams together and align their go-to-market (GTM) activities to accelerate revenue growth. It systematically optimises every part of an organisation’s revenue strategy and streamlines the people, processes and technologies that impact it. In this case, if a company is set on implementing AI, it needs to establish why it wishes to adopt AI, what processes it is trying to accelerate, how it can benefit all the teams that are involved and how this can contribute to the improvement of the overall business cycle.

Where to start - establishing a digital roadmap

The only way an organisation can go about doing this is by establishing a digital roadmap or a revenue lifecycle management framework. Essentially, leaders need to take a step back and establish their organisation’s digital maturity – that is, where it currently stands with regards to its transformation journey. Regardless of the size of the company, team leaders must first take step back and carry out a ‘situational’ analysis. This is necessary to better assess and understand where change needs to be made.

In doing so, business leaders will have a much clearer understanding of how data flows between their systems, teams and throughout various departments. Only then, will organisations be able to establish areas of improvement and fully optimise their overall revenue lifecycle. AI cannot add real value until

these changes have been made – businesses will simply be accelerating bad processes, potentially without all the data that they need.

Too often, businesses adopt new and emerging technology without clear direction or considering how it may affect departments within the organisation. Leaders must revaluate and analyse their existing operational model and identify any bottlenecks or inefficiencies across the revenue lifecycle. When considering all systems, teams and processes that are involved, rushing a transformation programme can result in major operational complexities and inefficiencies later down the line. In fact, a recent Gartner report2 revealed that up to 85 percent of all AI projects are likely to fail, with 70 percent of organisations experiencing little to no impact at all from their ongoing AI programmes.

Reviewing data flows and scaling AI

At the core of any transformation project should be the connection between people, processes and technology. No matter the size or complexity of an organisation or a department, business leaders need to establish a strategy centred around these three factors. In doing so, companies can identify, review and remove any operational issues existing within their business’ processes or legacy systems.

By eliminating operational inefficiencies and bottlenecks in this way, department leaders can then establish clear business objectives – such as automating contract and invoice management tasks, speeding up response times or improving their customer service. Budget constraints also can significantly impact the outcome of any transformation project. Therefore, it is important that businesses only invest in automation solutions that they can utilise effectively and that will positively impact their department’s overall performance.

How data is stored, managed and flows within a business’ operational cycle is vital to its everyday functions. Therefore, data is key to knowing when and how to begin implementing an AI or any technology for that matter. However, if the data is siloed or disconnected between departments, it can hinder overall operational efficiency and result in considerable revenue and data leakage. Before companies consider incorporating AI or automating elements of the revenue lifecycle, they must first streamline the processes that matter most to achieve long-term goals.

Unlock the value of AI – a phased approach

Ultimately, AI can bring real value to businesses. However, as is the case with any new technology or project, it is important that companies start slow and carefully consider their digital maturity to gain a true understanding of how it will impact their business. Taking a phased approach – and reviewing each process or department – will not only ensure the success of an organisation’s revenue lifecycle management and digital transformation journey, but it will also enable enterprises to recognise the true benefits of incorporating AI into their business.