INMA Study Tour on Artificial Intelligence

The International News Media Association hosted the 2023 INMA Study Tour on Artificial Intelligence, where 25 news leaders from 10 newsrooms attended. Madhavi Sekhri, INMA’s South Asia Division Head, generously invited me to moderate the two days. Here’s my roundup from the two days.

Meet the Cohort

The meeting was well-attended with 27 participants from 11 different newsrooms. We had representation from Product, Technology, Editorial, and Business departments.

1. From Jagran New Media, we welcomed Gaurav Arora, the COO, along with Subhashish Dutta, who serves as Associate Editor.
2. The team from Deccan Herald included their CEO, Shankar Sitaraman, and Pulkit Gupta, the Editorial Head.
3. Hindustan Times sent a robust delegation led by Aviral Mathur, the Chief Data Scientist, followed by Abhishek Sharma, the CPO; Amit Verma, the CTO; and Varun Bagga, the Head of CDP.
4. ABP News also had a significant presence with Subhamoy C. holding the position of CTO, Anindya B. as AVP, Arindam B. as CPO, and additional team members including Bishwajit K, and Debmalya D.
5. From Eenadu, we had Brihathi Kiron Cherukuri, the Director, and Khayum Basha, the Chief AdOps.
6. Amar Ujala was represented by Vibhas Sane, the Associate Editor, and Vikas Shekhawat, the AGM Product.
7. The team from Malayala Manorama included Santhosh Jacob, the Content Coordinator; Venkatesan Mohanam, an Architect; and Tom Antony, an Engineer.
8. Representing Sakshi Media Group were Anurag Agrawal, the CEO, and Kancharla Yadagiri Reddy, the Deputy Editor.
9. Anastasia Geydarova was the sole representative from Sputnik News.
10. From The Hindu, we had Manoj Kumar Venkatara, who works in Growth Product, and Nazir Ahamed, a Senior Product member.
11. Lastly, from The Times of India, we had Chandrima Banerjee, our assistant editor news, and me.

Each attendee brought a unique perspective from their respective positions, contributing to a diverse and enriching exchange of ideas.

Warmup Session

In the bus, I covered some material from my JournalismAI lecture.

2.1 Grounding Ourselves in Reality

News is a Low ARPU, Commoditized Business.

Surfing BigTech Waves

Additionally, the Environment Is Changing:

• Historically, computer science has provided storage, search, and data analysis capabilities. The expertise of understanding, applying, and generating content was almost exclusively within the domain of editorial teams. However, with the emergence of large language models, this dynamic is evolving. AI technologies are advancing up the value chain, venturing into territories that were once the preserve of editorial departments.
• Historically, news companies had to pay a form of ‘tax’ for discovery (SEO, Social) and monetization (Ad Networks). Increasingly, this will be supplemented by an ‘editorial tax’ in the form of ChatGPT or Bard API costs.
• Moreover, how our users interact with and access knowledge is changing. Chat interfaces are slowly replacing search. However, there is yet to emerge a clear strategy for monetizing chat interfaces.
• When this change in interface is coupled with the third-party cookie deprecation, it is likely that Search, Ad Networks and thus news publishers will lose revenue. For example, Stackoverflow — a media product to help developers — is constantly losing users due to GitHub Copilot — an AI LLM tool that answers developer queries.

Uncertainty looms large.

2.2 So Why Could You Invest in AI?

• Big Bet: Bet big in AI if you’ve a strategy to increase Average Revenue Per User (ARPU) or to reclaim strategic control with AI. However, can your competitors copy the same strategy? Do you have the cash to make it cost-prohibitive for competitors to follow you? If not, then in a small Total Addressable Market (TAM), not everyone can enjoy an increase in ARPU.
• Table Stakes: You could invest in automation. However, it’s important to realize that these investments may ultimately become as commonplace as purchasing Process Technology Improvements (PTI), Automatic Number Identification (ANI), DataWrapper, and incorporating Accelerated Mobile Pages (AMP) and Search Engine Optimization (SEO). Such technologies, though once innovative, are now standard practice and do not offer a competitive edge.
• Efficiency Bets: Lastly, ‘Efficiency Bets’ may seem alluring by potentially increasing the supply of content in Search and Social marketplaces to boost programmatic earnings. Nevertheless, this approach is unlikely to provide a sustainable competitive advantage. AI-driven marketplaces tend to balance itself out. For instance, Search and Social platforms may begin to down-rank AI-generated content, or the effective Cost Per Thousand impressions (eCPMs) could diminish over time. Therefore, it’s essential to monitor the unit economics on a weekly basis to ensure that the investment continues to yield the expected returns without diminishing in value.

Will Using LLMs Help Me Save Editorial Costs?

2.3 What might not qualify as a Strategic Bet?

Yes, news media is a low-margin business, but then so are big retail companies like DMart and Walmart. The difference is the retail businesses continue to own demand-supply variables that control their business, and hence every strategic investment can help drive down costs. In contrast, we’ve lost control to AI-driven marketplaces (Search, Ads) that auto-adjust every time we try to change something.

Don’t use the Peanut Butter Strategy

That’s an expectation that isn’t based in reality. Here’s why 👇

2.4 What might qualify as a Strategic Bet? Here are three examples:

Why Google invested in Gmail?

How Elon Musk is evolving Twitter

JSW’s Strategic Investment in IT

2.5 Thinking Outcome First

In each of the five, you’ll end up spending cash, but the outcomes can vary.

• You might not earn tangible cash from it. For example, many news companies tried investing in NYT Style immersive journalism in a half-hearted fashion but failed to monetize it.
• Some table-stakes investments like AMP, SEO-optimization, etc., will become must-haves but won’t give you strategic cash. Similarly, bad implementations of AI, like off-the-shelf personalization of one-off widgets, won’t move the needle.
• Then you could do deals with BigTech firms to speed up implementation in their marketplaces. However, it will only pay short-term cash. For example, a BigTech firm might pay you cash to create content for a new marketplace they are trying to seed. You will earn a good margin from it; however, in the long run, the BigTech firm will stop subsidizing once the marketplace is seeded.
• Other times, news media companies end up investing in assets that they do not have the leverage to monetize. For example, building costly CDPs and DMPs but lacking the sales force to
• Finally, there are waves like subscriptions which have an extremely low TAM in India. Hence, there will be only few winners in it.

2.6 How should you bucket everything you hear in these two days?

Bucket everything you hear into three categories:

• Automate. Use AI to replace your employees’ labor. This will eventually become table stakes in the industry, similar to the spends in PTI, ANI, etc. However, the first movers will end up burning more cash to make the AI just work! The laggards will be able to directly replace manpower with AI.
• Augment. Use AI to replace your employees’ labor and judgment. It will be extremely valuable but tough to prove attributable, sustained revenue from these investments.
• Transform. These are your strategic bets that may or may not work, but if they do, they could give you a long-term edge.

2.7 What should your decisions be?

Bucket everything you hear into four decisions:

• Hold: Ask upper management to keep observing this space! Be on the lookout for breakthroughs.
• Assess: Ask middle management to study it deeply with tangible details.
• Trial: Spend a small amount to pilot it with the goal of proving unit economics.
• Adopt: Spend a big amount to scale up the unit economics.

2.8 Should you Build or Buy?

I’d recommend picking one of two extreme paths—compute-heavy or compute-light—while acknowledging that adopting AI is fraught with challenges.

Buy

Buying AI is great for efficiency and table-stake bets. However, if you use it for a strategic bet, then consider:

• Your competitors can buy the same technology, thus eliminating all gains.
• If you tightly couple a strategic bet with a vendor, you’ll end up spending a ton of cash integrating with them and might not have the cash and bandwidth left to exit a bad deal.

Build

Building AI in-house can be a nightmare, too. Apart from the fact that it can get extremely costly, you might not have the staff and systems to get it right:

• News media companies operate technology that tends to have high error margins. For example, if your pollution tracker is off by 20%, it isn’t going to directly impact your bottom line. However, AI mandates setting up highly accurate data pipelines. News media companies tend to struggle with collecting data.
• News media companies tend to serve millions of users but through CDNs. Hence, they have limited muscle memory of building and operating compute-heavy infrastructures!
• Finally, all your stakeholders (bosses?) are used to operating deterministic software. In contrast, AI is probabilistic. Try explaining to your editor why certain stories are getting recommended to him and whether they should.

2.9 How are the two days organized?

On day 1, we will visit Big Tech companies that provide cloud infrastructures. Use these if you want to invest in strategic bets. Utilizing them will require you to spend a CAPEX (leveraging these meaningfully is a CAPEX at news media scale).

On day 2, we will have 10 small technology companies that will provide off-the-shelf tools requiring minimal integration. Use these as an OPEX for table stakes and efficiency bets until they are ROI-positive.

Day 2

On Day 2, we met 10 vendors at IIC.

4.1 Editorial

Using AI to Speed Up Video Creation

Next, we had Manoj Prabhakaran from Chennai-based TrueInfo Labs provide consulting services to implement newsroom efficiency solutions on top of large language models. They offer a varied array of solutions. This will help newsrooms pick and choose what is right for them and get it implemented.

Generative AI in CMS

Build Differentiation with Immersives

Finally, we had Anshul Pandey from Kalakari.ai. Anshul is one of the brightest NLP-based data scientists I’ve known for almost a decade now. He founded and continues to run the New York-based Accern. He is now in India and is setting up a number of different AI-based firms. Kalakari is using LLMs to speed up content creation.

4.2 Product

In today’s world, digital news companies cannot survive without products like Mixpanel, Clevertap, and Web Engage. These tools are critical to record clickstream events at scale, warehouse them, analyze them, and when required, segment them to send out targeted communication via SMS, Email, In-Apps, and Push Notifications.

There were two other vendors — the Langoor team presenting Quilt.ai and Conscent.ai. By this time, I was extremely exhausted and took a break. I will add their details in the coming week. If you were there at the study tour and want to help me write this part out, please DM. 🙂

4.3 Business

We saved the most insightful session for last. Here are insights from Sandeep Amar, the ex-CEO of Indian Express and now the founder of PDlab.me.

4.3.1 Monetization with Advertisement

What Percentage Of Indirect Revenue Comes To You

Automating Floor Prices To Grow Indirect Revenue

4.3.2 Distribution to Invest In

Micro-Celebrities Are Monetizing Their Social Presence

4.3.3 Content Strategy that Aids with Advertisement

All Brands Want To Advertise In Premium Spaces

I will wrap up now. These two days were extremely rewarding, especially the conversations with other cohort members.