Laying the foundations for a generative A.I. strategy that delivers value

Whichever viewpoint you hold, there’s little doubt generative A.I. has exciting potential for many organisations. It has the power to improve productivity, reduce menial tasks, create personalised experiences for customers and support better decision making by providing predictive insights.

But like all tech tools if it isn’t implemented correctly, generative A.I. at best won’t deliver a return on investment and, at worst, could damage your business. As more and more organisations integrate generative A.I. into their services how can you make sure you’re getting it right?

What is generative A.I.?

Before delving into the detail of how to plan a successful implementation, it’s worth defining what generative A.I. is. To give it its full name, generative artificial intelligence dramatically increases the flexibility and utility of A.I..

Traditional A.I. can interpret data and provide a programmed response, prediction or action, for example recommendations related to your purchasing or viewing history. Generative A.I., on the other hand, can produce new writing, coding, design, music, film, and so on, that reflects its training on huge datasets. In the blink of an eye a generative A.I. powered assistant could apply its knowledge to a completely new problem or brief and come up with a bespoke solution.

Of course, that brings challenges. For example, how can you ensure the information it provides is as accurate as possible and free from biases, how do you ensure it handles private data correctly, and how do you know which aspects of your business would benefit most from generative A.I. capabilities?

It’s not hard to imagine how a poorly planned implementation could lead to big problems.

Planning your generative A.I. transformation

At Riverflex our aim is to enable clients to benefit from cutting-edge technology in the safest way possible. We achieve this by developing a robust generative A.I. strategy as part of our data and analytics services.

Strategies will vary depending on your organisation and the sector it operates in. For some, particularly those in highly regulated industries, a high level of control needs to be maintained, whereas others may be able to push the boundaries in the pursuit of a competitive advantage.

For many a middle ground that balances risk and reward is the preferred way forward. This is the approach we took for a financial services company eager to explore how generative A.I. could enhance its services.

During the planning process, we shaped five key elements to guide its generative A.I. journey:

Customer and employee experience – This involved deciding how extensively generative A.I. is deployed in critical employee and customer interactions. The organisation’s appetite for risk is a key factor here. A startup may be more willing to invest in innovative personalised experiences and emerging technologies, whereas a more established company may focus on using A.I. to drive internal productivity gains while new capabilities are being proven.

Innovation operating model – Similar to the above point, firms with a higher risk appetite will seek to harness the benefits of autonomous, agile delivery teams and rapid releases to quickly evolve and enhance products. More risk-averse companies prefer to use centralised processes, stage gates, control systems and monitoring to make sure changes to live system environments are carefully managed.

A.I. technology and data – Understanding the business case and best use case for a technology before selecting which is right for your firm is the first step to a successful implementation. Platforms such as Orq.ai can then help you to assess, enhance and upgrade your capabilities, so you aren’t locked into one technology that may become obsolete. Orq.ai provides pre-built integrations to the latest A.I. and tools alongside centralised workflow processes that enable collaboration between cross-functional teams, making it easier to constantly innovate.

Risk and compliance – An assessment of risk should cover the full scope of your A.I. capability to ensure nothing is missed. But this needs to be balanced with pragmatism so that potential benefits to your organisation aren’t lost. Incubating innovation enables you to trial new concepts inside a safe set of processes. Experiments can be specifically designed to assess the benefits of a new capability in a way that protects the wider business and customer experience.

Governance – Again this is dependent on your appetite for risk. Those keen to embrace rapid experimentation and innovation will decentralise decision making to agile delivery teams. At the other end of the scale, centralised decision-making may be appropriate until capabilities and risk levels are proven.

Moulding a generative A.I. strategy that suits your business around these pillars is a crucial first step. Organisations that have fewer constraints than a financial services firm, may give more control to autonomous agile delivery teams that incrementally improve and release new products using cutting-edge tech and based on direct customer feedback.

A more cautious approach would limit the scope of A.I. to low-risk functions, introduce new tech slowly and reduce customer involvement to clearly defined stages in the process.

Developing a platform for ongoing success

Defining a clear approach that aligns with your team and business ambitions can lay the foundations for the adoption and scaling up of its generative A.I. capabilities.

A framework where organisations can safely trial innovation relevant to the sector, and put in place mitigation strategies that limit risks when new products reach the customer, can mature and prove its worth across the business. This in turn builds support for further investment in generative A.I..

As capabilities rapidly mature, this puts the business in a strong position to capitalise on innovation as it happens, keeping them one step ahead of their competition.

If you’re keen to harness the potential of generative A.I. to enhance your organisation, our experts can support you to develop an implementation plan that delivers the return you need at a level of risk you’re comfortable with.

Get in to touch for a chat about how we can help.