Let’s flashback to a scenario that some of you may know:
It’s 1999. The CMO of a large community bank needs to build a customer website. So he sends a memo to the CIO: “Get us online!” One year, (high) six figures, and lots of angry customer emails later, there’s a website that nobody uses. Money = wasted. Who did the CMO blame? The CIO and IT department. Why? “For building a bad website.”
It’s 2009. The CFO of a financial services firm agrees that the company needs to “figure out mobile.” So she approves an enterprise-wide “agile training” for the IT team, greenlights a bevy of new projects, and brief investors on the expected ROI. One year, seven figures, and plenty of negative app reviews later, there’s a mobile app that nobody will use. Money = wasted (round 2). Blame? Yeah, just like in ‘99, it falls on IT.
It’s today. The CEO of a multinational bank hears about artificial intelligence at a conference and doesn’t want to be left behind. So what is he doing right now? Drafting an email to his CIO and CC’ing your executive committee. “Let’s get on this AI thing!” You can tell where he and his team will be in a year – and they won’t be happy.
When business leaders abdicate responsibility for exploring the utility of new, bleeding-edge technology, the likelihood of success decreases significantly.
AI must be contextualized on the same technological continuum as the internet, mobile, and IoT. The implications and applications of this new wave are far-reaching and thrilling for your business, but the upside and the caveats are a continuation of the same themes brought forth by other technological revolutions: the opportunity for increased efficiencies, heightened utilization of personnel, smarter and faster decision-making, and richer operational profits. Not to mention the downside risk represented by disruption via technology-wielding upstart companies.
And just like with any other “new” technology your business has experimented with over the past 10-20-50-100 years, AI demands equal evaluation and stewardship from across the C-suite. Otherwise, you invariably fall into the same vicious cycle of technological innovation (and spend) divorced from business implementation (and value creation)!
So if you’re the CEO in the example above, and you’re about to punt that “figure out AI” email to your CIO with no follow-up or investment from you or the non-IT members of your executive team, then I have some seven-figure advice for you right now: just move that email to trash. Otherwise, you’ll just be wasting your money. Again.
Admittedly, this probably sounds like whacky advice coming from the head of an AI company. But I want to implore business leaders, particularly of financial service firms: don’t let your IT department waste money on AI because of your lack of involvement.
Because without your partnership and business-side guidance, many financial services IT departments risk making one of two critical mistakes when it comes to technology investments:
1. Sticking their head in the sand and not investing in Automation and AI.
This usually happens because either a) leaders (like you) espouse the “if it’s not broke, don’t fix it” mentality, or b) an organization just doesn’t have the in-house talent, or vision, to take on this challenge. Unfortunately, this ostrich approach won’t work, and these financial services firms will be disrupted by their more nimble competitors much sooner than they think.
2. Throwing money at automation and AI and hoping something sticks.
I’ve observed companies spending millions of dollars with very little, if anything, to show for it. While not as deadly in the long term as mistake #1, this slapdash approach can still hurt – not just from a short-term cash perspective, but also the opportunity cost of not investing around your core competencies and competitive advantages.
So how can financial services firms avoid these common errors?
First, read this: AI Playbook by Andreessen Horowitz. And now this: The State of Automation & AI Study 2017 (Horses for Source). And, finally, this: The Business of Artificial Intelligence (HBR). Great strategy primers, all.
Second, spend time with your front-line managers and directors in your call centers, your back-office support departments, and your IT support teams. Go to the place where customers, revenue, and your business all collide, find the suboptimal processes, and start with small pilots to incrementally explore how AI can help you automate your way to increased performance and liberate your people from manual rote work to focus on value-added strategic thinking. There’s gold in the hills where you least expect it.
Lastly, remember that you as a business leader cannot simply “outsource” your automation/AI investments to the IT department. Certainly, such investments need to be done in partnership with IT, but it’s no longer sufficient for the C-suite to throw it over the wall and hope the CIO and IT “figure it out.”
Automation and AI in financial services is not a fad any more than the internet is. The sooner you as a leader recognize it will be central to your future business model regardless of role and function, the sooner you will start taking ownership of setting the right strategy and budgeting accordingly. Please, business leaders, educate yourself and learn about the spectrum of options – from automation solutions that will provide in-year savings to longer-term AI investments – that can help you disrupt yourselves before you are disrupted.