How does the AI conversation play out in the boardroom? Is it a distraction? Automation by another name? The key to growth or a genuine existential threat? Ascent CEO Stewart Smythe shares his experiences.
As one of only 10 Microsoft UK OpenAI prioritised partners, we are currently helping customer after customer embark on Proof of Value initiatives, backed by boards who are keen to invest in ‘incubator’ approaches with a fast-fail charter.
AI techniques and progressive levels of automation have existed for years, but the success of ChatGPT has completely changed the game at board-level over the last six months. Boards are suddenly more interested and open-minded about what AI can do — following the trail blazed by leading tech innovators and cloud providers who see the movement as the next 10 sprints in the race for market share
I see three key reasons why AI is currently such a prominent board-level conversation:
Global tech hype and the scale of opportunity (and potential threat) that AI presents
Rising cost bases and declining margins as catalysts for investment in new intelligent automation approaches
Real-world relatability and relevance of AI use cases to business challenges and customer benefits.
1. Tech hype and the scale of opportunity.
This month, Microsoft announced over 50 new updates at their Build 2023 event, spanning ChatGPT; Windows Copilot; a new Copilot Stack with common extensibility; Azure AI Studio; and new data analytics platform Microsoft Fabric.
For Ascent, staying at the forefront of Microsoft’s AI movement is strategically critical, as we build on three years’ investments in developing an Azure AI pedigree. These include:
training and upskilling our engineering teams, introducing new learning pathways and certifications
providing a range of opportunities to apply these skills to new AI domains
building deployment accelerators, patterns and connectors for Azure AI
creating an AI Proof of Value (PoV) function for customers, and
participating in Microsoft’s specialist Data & AI leadership program.
As recently observed in Bloomberg Businessweek, Microsoft, as OpenAI’s largest shareholder, have stolen a march on other cloud and technology providers in this space and are laser-focussed on the ‘adoptability ‘of the AI wave. A natural consequence of this strategy is increased Azure consumption as businesses migrate their data to benefit from Microsoft’s AI toolsets and approaches to use cases.
Our customers are reporting AI-centric board-level conversations that demand unprecedented collaboration between business and IT, with ROI front and centre. They are approving exceptional spend and discretionary capital to advance AI this year, not just after the next budget cycle/2024-5. They are building committees and communities of AI champions and planning ambitious multi-year programs with incremental AI automation returns. The scale of opportunity is becoming clear — and looks like it will live up to the hype.
2. Rising cost bases, declining margins.
“How do we make a 30-40% productivity gain by deploying AI techniques?”. This is the million-dollar question for most boards right now, as they revisit traditional processes and cost bases with fresh eyes. Identifying new opportunities and use cases that enterprise AI tech can support is half the challenge. To ensure and accelerate success, boards need to build out delivery ecosystems that combine internal capability with experienced, credible external providers.
Our customers are facing an unprecedented erosion of profitability. The cost of money with interest rates soaring has pushed up ‘run the business’ cost bases, debt repayments, and investments in new initiatives. Post-pandemic habits have driven wide ranging operational changes which are still bedding in to deliver acceptable returns. Perpetual uncertainty, from climate change to war, is increasing the complexity of delivery core services, requiring greater agility and senior staffer expertise to remain competitive and valuable to customers.
Leaders know that AI-driven efficiencies can help mitigate staffing challenges. Application process automation can speed up workflows, interactions and time-to-market. Generative AI supports personalisation and improves search experiences. It can propose decision pathways that increase customer relevance, value, and competitive edge. Better business change and investment decisions are supported by AI, and informed by a wide range of ‘grounding’ data that is crunched and correlated through automation.
We have deliberately set a low barrier to entry in pricing and duration for our AI engagements: many of our customers are in exploratory mode and keen to take a bite-size approach to AI such as a PoV or hackathon, launching mini-waves of innovation that demonstrate value before building bigger business cases. This is part of a wider trend of boards prioritising large volumes of micro automation and search improvements that incrementally increase productivity, reduce cost and improve customer experience.
3. Relatability and relevance.
Most businesses are not technical pioneers, and there’s a long list of simple horizontal use cases for AI that many businesses (even the pioneers) can relate to. Our CTO Murray Foxcroft has identified some examples:
In isolation, these initiatives may not make the board agenda — but consider the impact of low-level yet widespread AI-enablement and adoption within an organisation, and the significant efficiency and performance gains to be won by hoovering up menial to medium-complexity tasks across business units become obvious. And that’s before you even start thinking about how AI can automate and orchestrate more complex interactions and deliver insight critical to corporate strategy and decision-making.
I have also recently observed that one customer anecdote inspires another. A senior leader at a customer organisation told me recently he liked the idea of AI, but couldn’t see any real opportunity for it in his organisation at present. Later I was describing a training course search bot we were building for a large professional services governing body — and it was as if a light switched on for him. He saw an immediate parallel with a requirement in his organisation. It’s easy to imagine that AI adoption at board-level will spread in this way: introduced by the mandate to create cost and effort efficiencies, but activated by anecdote.
AI is an active board-level conversation happening across all sectors. Early investments focus on identifying use cases and proving concepts that are capable of generating significant ROI, either through efficiencies and waste curtailment, or revenue growth.
Now is the time for business leaders and managers to experiment with use cases and automation ideas across their processes and divisions. Ascent has taken a set of strategic investment decisions to support this journey, making resources available to enable customers to play with AI concepts and build up confidence with proof points. We are also playing a key role in the innovation agenda with Microsoft, taking our people with us as we explore this really exciting space together.
Ascent’s approach to AI.
Our technical AI strategy focusses on the practical application of OpenAI’s GPT-4/ ChatGPT and Microsoft’s Azure OpenAI service to common customer use cases. Our approach is to quickly prove value that can be scaled over time proportionally with trust. This helps customers derive deeper meaning and value from their known and latent data assets in a responsible and sustainable way.
Our big bet is combining the power of the Azure cloud with Open AI’s leading-edge capabilities and our practical skillsets, AI-optimised infrastructure, patterns and accelerators. We collaborate closely with customers, helping to identify and prioritise use cases for AI, predict ROI and explore prototypes before moving into production. We then measure, understand and optimise results and experience.