Navigating the Noise of Innovation

The emergence of Generative AI over the past two years has unleashed an overwhelming flood of information, new tools, vendor pitches, and leadership pressure to move faster.

The volume of which is unprecedented.

Having spent several decades helping organizations adopt and scale emerging technology, even I’m overwhelmed by the speed at which Generative AI has emerged and new capabilities launching.

So, not surprisingly, the most common question I get asked from colleagues is . . ."How do you separate the noise from what's important?”

This prompted me to create "Through the Hype," a newsletter, dedicated to helping organizations cut through the noise on what matters, why it matters, and how to act on it.

This inaugural edition provides a framework to help those responsible for innovation navigate the abundance of information successfully by focusing on what’s important.

Noise of Strategic Importance

"The art of being wise is the art of knowing what to overlook." - William James

First, focus on the noise related to emerging trends that directly impact your strategic priority. Or should I say, an emerging trend that has a potential use case that could directly impact your strategic goals.

Before reading, downloading or subscribing to any source of information regarding emerging trends, start with “what are the goals of the firm (department or team)” Any noise that doesn’t align with it – is just that, noise.

Sure, innovators must track future trends beyond current priorities, you just need to align your attention and initiatives proportionally to the innovation horizon of the emerging capability.

Example: All the hype related to the Metaverse is a perfect example. Two years ago, consultants, vendors and the media pushed the future of work as a “virtual office”. Even Facebook renamed the company to Meta.

Yet, use cases (for most organizations, including financial services) were primarily limited to HR and training/onboarding. Unfortunately, not the ?use cases where the value would justify the cost to implement, maintain and upskill / train.

Industries such as the medical field made perfect sense because it allowed them to create a virtual environment that could not otherwise be available. ?Recreating an office conference space . . .not really that critical.

When use cases for emerging capabilities don't align with strategic ambitions, securing budget becomes nearly impossible.

But that doesn’t mean you ignore the trend. Your role as an innovator is to maintain enough surface-level knowledge to provide regular insights to stakeholder as the trend matures, while preserving your focus for more strategic experimentation and pilot initiatives.

Once a use case appears – that’s when it moves to the next innovation horizon – experimentation.

Noise That is Overheating

"Never begin cooking when you're hungry; by then it's too late." - Julia Child

Several years ago, I advised a startup that visualized momentum in topics or "chatter" across public data sources like Twitter and Facebook. Their tool created dynamic bubble clouds that grew in size as discussions intensified.

It was actually quite cool, and useful.

The London Olympics, a client at the time, used the tool to track real-time attendee conversations. Hovering over a trending topic (like Michael Phelps's multiple wins) revealed what people were discussing, even if you weren't at that event.

Unexpectedly, organizers discovered its real value: spotting facility issues early, helping them address attendee concerns before they escalated.

Solving a problem before it becomes a very visual problem? Golden!!

Tracking emerging technology trends follows a similar pattern. You don't want to be caught off guard when a trend becomes too hot to handle. Having an emerging trend radar is critical to monitor rising temperatures to know when to start paying attention.

Why is having a temperature gauge (or emerging trend radar) useful? Look at the example of ChatGPT and Generative AI.

Organizations that were actively tracking trends were already experimenting with synthetic data and pair programming, both Generative AI tools. They probably had already written up a Trend Report about Generative AI to give to senior leadership.

Those without radar systems?

They were caught flat-footed when executives started asking about ChatGPT after reading about it in the New York Times - never a good look for an innovator.

Modern platforms like IONIC and Mapegy track emerging signals systematically, helping organizations spot rising trends before they peak. While these enterprise tools are powerful, even a basic “home made” solution using AI and low code can create effective trend monitoring.

Emerging Trend Radar

The key is detecting trend temperature early and understanding how trends relate. When signals sustain over time, they demand attention. You don't want your first briefing on a trend to come from a CxO who just read about it in the Wall Street Journal.

By that time, you’re too late.

Noise Based on a Bullshit Meter

"The most essential gift for a good writer is a built-in, shock-proof, shit detector." – Ernest Hemingway

Now that you prioritized "what" to pay attention to, you need to know where to go to get your information and "how much attention" to give the specifics that are coming out of it.

Sources for emerging technology information typically fall into three buckets:

1. Typically objective and researched based (Academic, Premium Research)
2. Hands-on expertise, but with some bias (Consulting / Tech Partners, Expert Communities)
3. Attention-grabbing noise (News Media, Promotional Content)

The key is creating your own BS meter in knowing how much weight to give each source and when to dig deeper. Here's what I've learned:

• Prioritize peer-reviewed or research data-backed insights
• Value hands-on implementation experience
• Be skeptical of hype cycles and vendor claims
• Track sources that consistently provide value

And one of the most important. . .

• Cross-reference some of the claims you hear across multiple source types

When I read recently, in a major publication, that a large financial institution has already launched 500 generative Ai applications (I believe it was Visa?). . .I took it with a grain of sale.

But remember, leaders are reading major publications, so you can’t ignore the noise, but have enough common sense to be able to answer why it’s just noise with solid data.

The Innovation Intelligence Matrix

Putting It All Together

Success in navigation emerging trends means having to make choices on what to pay attention to and what not to. It comes down to three things (and a whole lot of gut instinct):

1. Strategic Value - If there isn’t a potential use case this emerging trend supports that aligns nicely with your strategic ambitions, it's just noise. Pay attention proportional to its potential impact.
2. Temperature Gauge - Detect rising trends early by monitoring signals across multiple sources. You want to be experimenting while others are still reading about it.
3. BS Meter - Know which sources to trust, what to trust it for and how much weight to give them. Cross-reference claims and validate with trusted partners.

Put your energy and resources on innovations that actually matter.

What noise are you struggling with or keeps you up at night?

Follow me on LinkedIn for weekly insights, subscribe to "Through the Hype" newsletter, or DM me - I'm always eager to help fellow innovators cut through the noise.

Darlene Newman