‘Future-back’ business thinking for generative AI transformation

While it’s understandable that some businesses have implemented a firm-wide ban while they get to grips with generative artificial intelligence (AI), this approach is unlikely to serve them well long-term. Nearly half of our survey respondents told us that they feel that generative AI is a major disruptive risk to their current business model based on what their competitors are planning. How, therefore, can organisations position themselves to effectively exploit generative AI, navigate the associated risks, and not just survive the transition but really thrive?

Strategy in the age of digital knowledge

Digital transformation has been a key strategic driver for efficiency and productivity over the past few decades. As we move into the next phase of the information age, these digital and data strategies are only becoming more fundamental to business success.

The launch of free and easy to use generative AI tools has had a profound impact on digital strategies. The incredible excitement around ChatGPT and other large language model (LLMs) tools seems to have penetrated into societal and business consciousness extremely quickly. 70% of our panel of middle market business leaders said that not only do they understand generative AI, but also feel they would be able to explain it to someone else, with a large portion already using the freely available tools in their operations.

This significant impact will catapult all AI, both predictive AI and generative AI, to a tipping point, making it even more essential that firms quickly embrace these new tools, work to curate their proprietary data and to develop their workforces and talent. Those that don’t risk losing out to those with greater human and machine intelligent decision making.

Policies in a digital age

While uptake of this technology has been greeted with widespread enthusiasm, for some it has been alarming. Italy took the bold step to ban the technology entirely over fears it would decimate the workforce, and there have been widespread calls to halt development of generative AI technologies until its impact is better understood.

These fears are not unfounded, however only 58% of our survey respondents said they already have a generative AI policy in place, leaving a large portion of the middle market exposed to the risks of both not embracing and not managing these new tools effectively and safely.

Businesses need to adopt a ‘twin’ approach. On the one side, experimenting with where generative AI provides a competitive advantage, and on the flip side implementing guard rails for ‘safe experimentation’ by utilising robust data privacy and protection measures.

‘Future-back’ thinking

The key to drafting these strategies and policies is to embed a future focused mindset – what we term ‘future back’ thinking. Businesses need to cast their mindset to the future and consider the strategies and operating models they are going to need to succeed by looking at a number of elements in an integrated manner: how they want to deliver their services, and how they want to interact with their customers, suppliers and staff.

Much of this change needs to start from the outside looking inwards. Businesses must consider the entire ecosystem they operate in, what their position could be and, crucially, what combination of human and machine capability will be required to create a digital operating model that is future fit.

The cohabitation of human and machine

Businesses that only consider either the machine or the human (people) element on their own will struggle. More than ever a multidisciplinary approach is needed, where the digital knowledge age winners re-imagine unique future ways of working to a place where tasks are optimised through the cohabitation of people and technology.

There is an understandable association between new technologies coming in and employment being threatened. With generative AI that thinking needs to evolve to one where the disruption to employment is seen as equal to that of the opportunity of the augmentation.

Humans and generative AI capability (in the form of algorithms) collaborating is not just about being able to process larger amounts or data. But rather to work together to create wisdom in decisions that deliver greater performance or minimise risk. Those that build these cohabited models will create more intelligent functions and more intelligent organisations.

The risk to language heavy businesses

For the organisation’s whose business models rely on language and text as an output, potentially the greater the risk of falling behind competitors that embrace generative AI. The impact of generative AI on the legal profession makes for an interesting case study.

Huge parts of legal work are done using language heavy documents, for example, contracts, petitions, agreements, letters or legislation. Forward-thinking law firms have collaborated with an ecosystem of generative AI service providers (Tech and Law Companies) to create tools and platforms that generate effective first draft contracts or agreements. In having the generative AI tool produce those documents, (that are time intensive for a human to put together) valuable time is then liberated for the legal professional to dedicate to creating an even more effective version, and being able to decide more quickly how they want to position their negotiation.

These improvements in time and intelligent decision making will kick-start a real shift to humans performing more intelligent functions and moving away from the more routine functions. What will drive the real winners will be those that have enabled AI to provide them with the fastest decisions, the most insight and the most validated information as part of cohabited legal tasks.

Finding the balance between safety and innovation

The key to success with generative AI is for businesses to implement a twin strategy. Leaders shouldn’t seek to control generative AI - it can’t be controlled. But rather to use the enthusiasm and curiosity surrounding generative AI to create a space where employees can experiment, innovate and up-skill within the framework of well positioned policy guard rails. This will create a path to where employees and generative AI are enabled to work collaboratively and help organisations navigate the digital age.