How to prepare for the impact of AI everywhere

Generative AI is ushering in a new wave of computing in business – here’s how we can retain trust in and through AI while driving innovation

When it comes to AI, we are reaching an inflection point where entire industries will be redefined, and a new era of GDP growth will be unleashed. Generative AI – specifically Large Language Models (LLM) like GPT popularised by OpenAI and Microsoft – is the catalyst, as we see it democratising AI for the masses. This means AI is now available for everyone to use as a pervasive ‘copilot’, creating new opportunities for human workers, organisations, and society at large. It will revolutionise the way we complete tasks and reinvent business processes.

Pervasive AI is becoming realised because organisations accelerated their move to the cloud. With the good-enough data platform and governance built during their journey-to-cloud, organisations can shift their focus to extracting value-in-cloud. This is where AI comes in: it can deliver such value, creating an accelerating and pervasive AI-first world providing the ability for wise adopters to address real opportunities and create durable competitive advantage. To help their business seize this momentous AI opportunity, enterprise leaders must adapt an AI-first mindset. Read on to learn why, and how to get started now.

Pervasive AI: prepare for impact

Here are 3 reasons why we are so bullish about the impact of AI:

  1. AI will empower organisations to address difficult problems by taking advantage of the world’s knowledge across company boundaries, and within the proper legal frameworks. Imagine AI reasoning across the knowledge corpus of companies that traditionally have worked together, may have shared data, but not practiced ‘shared cognition’. For example, a manufacturer who creates a new material for tires because of multiple shared knowledge corpuses across the manufacturer, government, a chemicals company, and the investment arm of a financial services company. AI-First is the growth engine for multiparty systems greatly extending the data footprint and capability of a single organisation. And instead of just storing and analysing data like many companies do today, new cognitive AI models can keep the data “alive”, creating a constant feedback loop (but also a need to manage the risk of more “digital noise”).
  2. AI will force a rethink of the relationship and engagement between people and technology, perhaps as significant as during the Industrial Revolution. AI-first is inherently people-first, impacting everyone and blurring the distinction between ‘knowledge workers’ and ‘blue collar workers.’ The level of machine cognition is now good enough that we can tap into the vast “librarian” of the internet and combine with hard-to-navigate “locked away” enterprise knowledge stores for creation of new content or seeking/finding answers. The notion of having a copilot or assistant is realised, revolutionising how we think about task completion and business process reinvention. AI decisions will however need to be uniquely woven from a company’s values. Successful leaders will be the ones who deeply understand how to leverage AI to support employees’ creativity and quality, and share lessons about how employees can use these models to strengthen their sense of workplace contribution and value. We will need to ensure that we don’t create new distinctions between ‘augmented’ and ‘non-augmented’ workers. We will perhaps need new team structures and new organisational models.
  3. Speed and Scale. Speed is not just about computer chips being 100.000X faster than electric signals in our brain (although they are!). It is about the vastly accelerated time-to-value we’re already seeing in the initial real-world use cases. Looking ahead, we believe this acceleration will expand from discrete AI projects to encompass the rhythm of business itself as creation and intelligence will occur at the speed of computers and at the hyper-scale of cloud. Another dimension is the intense competition (and cooperation) in the ecosystem, and the learning-by-doing-at-internet-scale which is accelerating innovation. The limitations of today may seem trivial tomorrow.

How your organisation can start adopting an AI-first mindset today

Organisations are facing a tough reality of transforming to respond to today’s unpredictable market forces, while also preparing to perform and grow in the future. As digital leaders navigate this new era, we believe five key factors will help them on their journey:

  1. AI is an assistant to, not replacement for, people. For AI be a useful copilot, employees should learn how to iterate from generated concepts that need to be tweaked, refined, enriched and approved. The bigger opportunity will be to achieve the promise of the future of work where humans flourish. The best will go further and ensure that AI contributes to social goods like healthcare, education, financial opportunity, and more. This is planetary-level change enablement leading from the front.
  2. Be clear on the business “why?”. Short-term, we see the most common AI-First scenarios including: 1) improved customer sales and service; 2) operational cost reduction with document/image generation and process automation; 3) real-world employee productivity with enhanced knowledge management and routine task automation; and 4) better/faster software development. We recommend selecting the initial use case where these capabilities can be integrated in a modular, yet scalable, way and ideally where you already have an existing capability, like an existing chatbot. You should also start where the data is qualitative and diverse, because…
  3. Remember that it all starts with data. It is critical to think about data as having the potential for intrinsic value if treated as a product that can unlock its dormant value. This requires the breaking down of data silos, removing duplication, creating trusted data products, reducing the cost of data rework. Perhaps most importantly, it requires the democratisation of access by more widely sharing high-quality data products across the ecosystem.
  4. Trust is paramount. That means trust in technology, but also trust through technology. These changes are having a tremendous human impact, and the potential for unintended consequences will create ethical dilemmas that the world does not yet have robust standards or legal precedent for. It’s not enough to repeat the mantra of “do no harm”. It’s now critical to programmatically embed digital ethics into your organisation and processes today. Key topics to focus on are: 1) robust, ongoing risk-based oversight; 2) respect for intellectual property; 3) solid information security and privacy; 4) transparency and explainability; 5) sustainability; and 6) intentional sourcing.
  5. Experiment courageously and wisely. Adopting an AI-first mindset won’t happen overnight, and we may not know what we don’t know. Sometimes use cases can only be discovered by experimenting. We’re certainly not promising to know it all, but we can help you take some practical actions to move your organisation and people forward.

Today’s generative AI use cases

As early testers, adopters and builders with Azure OpenAI and other AI technologies, Avanade is actively working with business clients globally that are harnessing generative AI. Below are a few examples:

  • A service company is comparing the performance of generative AI models with established customer document validation approaches (e.g., compliance, completeness and accuracy), for tasks like intent classification, key extraction and text normalisation.
  • A non-profit organisation is looking to deploy generative AI as a copilot to generate grant reporting – cutting staff’s time spent on manual, administrative duties and helping them focus more on tasks that have a greater influence on the bigger picture.
  • An oil and gas company is looking to bolster knowledge management and search results on trouble tickets, bringing together generative AI and the existing enterprise infrastructure.
  • The technology can be used to help manufacturing industry designers, engineers and marketing teams create and develop new and innovative product design ideas.

This is just the beginning, and it will only become easier to create better ways of working that increase efficiencies and free employees to focus on higher-value tasks and personalised experiences. With the recently announced AI Copilot from Microsoft, powered by GPT-4, able to generate entire reports and presentations based on prompts, expect generative AI applications and use cases like this to become prevalent in the everyday lives of employees over the coming 12-18 months.

Get started with generative AI now

Avanade has been working with OpenAI since its early integration with Microsoft, offering deep Microsoft expertise, from data and AI to Azure. The AI models will become even smarter and more flexible, so organisations need to lay the groundwork and start testing now to leverage the best of generative AI in a responsible way.

If your organisation seeks to cut through the hype and learn, explore and build with the latest generation of AI tools, Avanade can show you first-hand how generative AI and an AI-first mindset can create transformative value at your organisation. Contact us today.

Florin Rotar is chief technology officer at Avanade.

This article was written as part of a paid content campaign with Avanade.


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