Since generative AI exploded into the hype cycle, enterprise companies have been racing to find ways to adopt it. This level of enthusiastic investment is understandable given McKinsey’s estimate that among industries globally, gen AI could add the equivalent of $2.6 trillion to $4.4 trillion annually in value across the 63 use cases it analyzed.
On the flip side, generative AI is only as good as the data that feeds it. LLMs and MLMs have had something of a free-for-all to absorbing vast amounts of data and publicly available information. Are businesses paying enough attention to the risks and guardrails, in the pursuit of ROI and impact?
One vendor taking the matter seriously is data analytics and integration vendor Qlik, which announced the establishment of its inaugural AI Council this week. The initiative brings together a group of AI experts from around the world, with an emphasis on embedding ethical AI development.
Qlik has a long history of talking to customers and experts in the market, and bringing the data community together to share and develop tribal knowledge. According to James Fisher, Chief Strategy Officer:
We have a long standing Executive Advisory Board, which is made up of senior leaders from our largest customers, both across the business and IT. This was a very natural extension of that type of thinking - making sure that we've got a group of incredibly seasoned individuals that span academia and the enterprise to help us move forward is key.
It takes a village
When I spoke with Fisher at QlikWorld last year, we discussed that executive advisory board and its cross-industry demographic, with members from the United Nations, Ford and Syngenta to name a few. The AI Council includes pioneers and world-leading authorities including Nina Schick, Dr Rumman Chowdhury, Kelly Forbes and Dr Michael Bronstein. Its goals are clear. Fisher explains:
I think it's easy to misconstrue an initiative like this as our opportunity to try and shape the world. That's not what this is about. There has to be a huge ecosystem around AI ethics, around governance, how we establish trust, just as we saw with the data literacy movement, but no one group can really own that. The same is true around the evolution of AI - it takes a village to change the way in which we look at data, to change the way in which we look at AI.
Members of the Council will work within Qlik to guide the company’s R&D direction, inform its product roadmap and ensure its customers’ use of Qlik’s AI is built with a focus on responsibility and ethics, says Fisher:
This is about making sure we're part of that conversation part of that narrative, that we understand it. And we're internalizing that in terms of everything that we're doing. It's as much a connection point to that wider ecosystem, as well as our own vision for how we believe we should work and how we should help our customers work with data and AI.
A comment from one member of the AI Council, Rumman Chowdhury, helps to drive home the point:
We’ve reached an inflection point where innovations like generative AI are impacting the world as the internet did. This is not the time for complacency. ‘Adopting AI’ is not as simple as some suggest, but getting left behind is a risky game. By taking responsible steps, organizations can enter an era of unprecedented innovation – I look forward to being able to contribute to this evolution.”
From BI to AI and back again
This latest step reflects an ongoing theme of trust in data and technology. Qlik’s emphasis on responsibility and governance was a key message last year among customers and partners. It’s natural for the conversation to shift to the critical nature of data quality and lineage in a world of AI, even more so as data continues to be increasingly democratized across organizations.
According to a recent benchmarking report from Qlik, 31% of senior executives plan to spend over $10 million on generative AI initiatives in the coming year and 79% have already invested in generative AI tools or projects. But without the right data strategies, the threat to data integrity and business operations will increase.
Focusing on the problem that needs to be solved comes back to Qlik’s modus operandi, Fisher confirms:
For me, that's part of the DNA of how we approach all of the problems, just as we've approached the evolution of big data, then into the evolution of migration to cloud. And now we’re back talking about big data again, and what that means in the context of gen AI, and how that's shifted the goalposts is incredibly relevant to how we think about things.
The question now is how these conversations are resonating with Qlik customers, and where their goals sit in the space between AI adoption hype and potential pitfalls. Fisher observes that at the beginning of last year, there was a rush towards what he described as "science projects" around this, with an undercurrent of, ‘We have to do something, so we'll just do anything’. That's changing, he says:
I think as we now start to move beyond science projects, customers are asking us pretty consistently: ‘Okay, what do I do next? Where do I start that journey?’ We've always said that there’s so much data out there - the question is, how do you now curate that in a way that it can be useful for AI and can be trusted for AI?
That's why we've spent a lot of time working on how we establish that foundation, how we help customers create those data products, how we can then augment our pipeline to reduce human errors, and then longer term how we add more technology to address the problem. That sequence is very important to that value curve.
It has been a busy start the year for Qlik. Last week it acquired Kyndi, an innovator in natural language processing, search, and generative AI, bringing Kyndi's CEO and leading AI experts as part of the acquisition process. After acquiring Talend in May last year, there are no signs of slowing down. Amid the momentum, what’s next? Fisher says:
The opportunity now is to really pull all of these different components together. We invested a huge amount over the last five years or so, in building out our cloud platform, giving high levels of stability, a unified interface, giving a way for people to interact, not just with the terminology, but with Qlik as well with the feedback, customer success, and onboarding components that are part of that.
Talend has been a big asset in helping to embed all of those components in the platform, he confirmed – this, reinforced by the AI Council creates a hub of technology that can help customers to identify new use cases.
CEO Mike Capone called the formation of Qlik’s AI Council a “strategic leap, reflecting our deep-seated commitment to not just advancing AI, but doing so with ethical integrity and practical applicability".
Based on diginomica’s Year in Review of AI Use Cases, it's clear we need to see more emphasis on accountability and discipline across the enterprise. During my conversation with Fisher, we talked about the annual January tradition of predictions for the year ahead that are still doing the rounds. These often begin with a wearisome trope: “What do we predict for the year ahead, Bob?” “Well, Jeff, you won’t believe this, but it’s everything we already do!” We agreed that to some extent, 'Software wags the trends, as opposed to trends wagging the software'.
Predictably, generative AI is high on most trend lists, as executives are looking for use cases that can be implemented quickly. Risk management and responsibility seem to be a little lower on some of those cheerleading lists. Thankfully there are some companies who are clearly giving this the important focus it deserves.