AI: Where We Stand

Signal vs Noise, Part 3.

AI is everywhere, all at once. It’s a bit overwhelming so we’re working together to find the signal within the noise.This note is one of a multi-part series of emails, events and discussions where we start to split the AI hype from the opportunity and how it applies to the growth of a recurring revenue business, particularly in terms of the customer experience.

We asked for your thoughts on AI at the moment — questions, concerns, etc. — in order to better shape this conversation around what matters to you right now. Here’s what we gathered from the community:

Describe your current understanding of what AI means for your customers and your business?

Respondents to the survey are clearly AI curious, everyone reports having some knowledge but no one considers their POV — logically, this is to be expected, we’re learning together.

What is your role within your company?

The C-Suite and Managers were most involved in this survey with few Directors providing input. Among them, mostly Product and Marketing folks. This is somewhat consistent with the BCG study that found leaders may be getting ahead of their teams on AI.

Almost all respondents represent recurring revenue products with a significant lean towards news media and publishing. That bias is important to note as we see the news media and publishing at the forefront of consumer (non B2B) exposure to AI — this is where consumer experiences and expectations are starting to be conditioned.

Most of the respondents are looking to learn in three general categories:

1. Work efficiency

   • “Will AI be able to replace some facet of the human editing process in a news/publishing organization?”

   • “How can generative AI boost efficiency and effectiveness of the management of people, processes and initiatives?”

2. Examples

   • “Would really like to learn how other content creators are using it.”

   • “I would like to see explicit, objective breakdowns of processes without salesmanship or hype.”
     

3. Customer Experience

   • “How might AI expand our service offerings?”

   • “What are the customer-facing applications that improve user experience?”

So here’s what we’ve gathered as signal in these areas of interest, through HoK’s lens of customer experience optimization. Side note, public statements on the topic of AI are highly recommended for customer transparency — you may have seen this study from May that 50% of newsrooms are using AI while only 20% have any guidelines, not to mention any public transparency about how it’s being used to produce the news!

HoK’s current #1 priority regarding AI is the protection of trust and the people who cultivate it with integrity — journalists are on the front lines but consumer brands are next, and as people whose business is customer experience optimization, we’re trying to lead by example.

How Can AI make work more efficient?
Right now, that’s tricky. The promise exceeds the current reality in most cases because there’s a learning curve and we’re just at the beginning of it. The outputs are a bit limited but getting better very quickly. We’re certainly on the precipice of real impact, and some consider the recent layoffs directed at LA Times copy editors as the first wave.

The current struggle is “prompt engineering”, ensuring that the input to the AI, the prompt, is effective at producing the desired outputs. This seems easy at first pass, but anyone who has tried to get real value quickly learns that it takes some time to produce a quality output that could have actually saved you time. The level of effort is proportionally higher than the level of impact as we learn how to use the tools, but that’s also changing quickly. And the market is already looking beyond prompt engineering skills to the application of those plus the integration of processes that provide real valuable returns, referring to this as AI Operations.

Leaked upcoming features from OpenAI, and comments from their CEO have confirmed that they’re going to aim for the B2B category, and suggest that MS/Bing will focus on the consumer applications (likely to evolve the search advertising model). That said, keep an eye on OpenAI’s ChatGPT For Business in the coming weeks and hold off on any annual AI contracts for the moment.

Show me Examples

• Heres some insight to Insider’s approach to AI in the newsroom

• CNET had quietly begun producing articles with generative AI systems, now it is clarifying how it will — and won’t — use the tools in the future.

• This Northwestern Professor is gathering a library of examples for us to keep an eye on

• I recommend following Rachel Woods on Linkedin, she’s the founder of The AI Exchange and shares lots of great examples. Rachel is emerging as a legit leader amongst the self-proclaimed AI experts of the moment.

Customer Experience

There’s a lot less focus on the customer experience applications of AI, outside those looking to make work more efficient. But there isn’t much on the market that’s reframing how AI is improving the experience of an existing product that fits a typical consumer need. Chatbots are the dominant interface at the moment — they’re growing insanely fast — the best examples I’ve seen so far are Khan Academy’s Khanmigo and Skift’s Ask Skift. Snap has its own chatbot and instagram is working on one, to give you a sense of scale for this interface and the user expectations on the horizon. If you have other examples, please reply and let me know so I can share with the group in an upcoming newsletter.

But generally speaking the current focus is on internal chatbots. They are lower risk without facing customers and they can leverage large knowledge bases of text that already exist in company servers. This is where lots of experimentation is happening right now. Legal considerations and guidelines for use (see the note above) could prove sticky, however.

We’re eager to develop in this important space, to use AI as a chatbot or another manifestation, for customer experiences that build credibility and trust as a means to more sustainable commercial relationships, guided by questions that are yet to be answered:

• How does AI improve the customer journey and where does it make the biggest contribution — acquisition, engagement or retention?

• Should AI products be free or paid?

• What’s the risk of widespread fraud to our customers or our brand?

In the next installment we’ll dig more into the emerging chatbot alternatives and any other topics of interest — feel free to reply directly with topics, suggestions or questions on your mind.

Thanks
- Matt

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