From September 21 to 23, Bangalore played host to India’s biggest AI Conference – Cypher 2022. As one of the largest gatherings of influential innovators and vendors in the country’s burgeoning AI industry, it was an event that we certainly didn’t want to miss.
Throughout the event, numerous speakers explored the latest advancements and trends across every aspect of AI. There was a lot to learn, but here’s a quick rundown of our top takeaways from Cypher 2022, from our analytics experts Disha Kumar, Sameep Rohatgi and Saikat Bagchi.
1) Humans aren’t going anywhere
One of the most reassuring trends we observed across the event is that many leaders and organisations seem to value and respect the critical role that humans have to play in enabling AI success. In the past human intelligence (HI) has been somewhat removed from the AI conversation, but now that seems to be reversing.
There was a lot of discussion around ‘human-in-the-loop’ AI, particularly around how it helps turn AI outputs into actionable insight – providing vital context that today’s AI use cases need to deliver business value.
HI is one of the cornerstones of The Smart Cube’s AI+HI approach to intelligence and analytics delivery, so the team found it very personally satisfying to see our way of working validated by other leaders in our industry.
2) While technical skills are growing, they must be aligned to business requirements to optimise the impact and ROI of digital transformation
Many vendors and in-house AI teams are reaching extremely high levels of technical skill and pushing the boundaries of what’s possible with AI and machine learning (ML). But there still seems to be less focus on the importance of contextualising technical solutions with pertinent business requirements.
Models and capabilities built purely on technical knowledge are powerful in theory. But to deliver value and ROI for the organisation, those capabilities must be aligned with how teams work and what they’re trying to achieve. If they’re not, that’s how you end up with underutilised models and abandoned AI-based digital transformations.
To ensure that alignment, teams need the right blend of technical skills and domain knowledge. They should understand what the function they’re empowering wants to achieve, and have the technical knowhow to apply leading AI approaches and models to make it happen.
3) AI needs data, and innovators are getting creative to source more of it
To have a transformational impact on an organisation, AI needs large quantities of reliable, clean data. As teams’ AI and ML efforts have matured, many seem to have hit the same speedbump – running out of that kind of data.
Augmenting your AI capabilities with new data types and sources can bring vital context to the outputs you generate, helping to elevate them from basic observations to timely and actionable insights. At the event, we saw numerous innovators employ creative strategies to bring in more of the data they need, when they need it.
Data crowdsourcing appeared to be rising in popularity, both internally (tasking domain teams with sourcing more of the data they need) and externally (working in collaborative groups to share valuable data points).
If opportunities to pursue strategies like that are open to you, they certainly appear to be valuable. But not everybody can crowdsource, and it’s worth remembering that if it’s valuable data you need, there are plenty of expert partners and curators that can provide it.
4) To get the most from AI, we first need to change how people think
Another very reassuring trend we noticed at Cypher 2022 was that a large number of organisations now seem to appreciate the ‘people’ change that’s necessary to get the most from AI and ML.
Numerous speakers put a strong focus on change management, and how we can support teams through the changes in workflows, processes and practices that come along with the adoption of new AI use cases.
Careful change management is an essential element of any AI journey. AI should empower people and augment HI, so it’s critical that teams are upskilled and supported through the AI adoption and implementation process.
By bringing teams on board early and using their input to shape how their organisation uses AI, leaders can ensure their AI use cases deliver value in the right ways. But more importantly, that can also inspire teams to find their own use cases for AI and organically expand how it’s applied across their domain.
5) AI and analytics maturity are growing, but the picture isn’t the same across every function
If you only look at areas like sales and marketing – functions with a wide range of AI use cases – you might conclude that today’s organisations are reaching very high levels of AI and analytics maturity. But, from what we saw at the conference, the picture doesn’t look the same for every area of businesses.
Procurement and supply chain for example were relatively underrepresented – despite being domains with high AI transformation potential. Once again, that could be down to a lack of domain expertise, or a disconnect between the organisation’s technical and domain experts.
If an organisation’s digital leaders or AI partners don’t understand exactly how Procurement could be empowered and transformed with AI, they’re powerless to achieve that — no matter how strong their capabilities are on paper.
To read more views from The Smart Cube about combining AI and HI to drive business value and make the most of the AI opportunity, visit our website.