Revolution Has Its Consequences: GenAI Is No Different

The launch of ChatGPT by OpenAI in November last year upended how content is created in marketing, journalism, design and education, and in fact, everywhere that content is produced.

But as with many revolutions, the long-term consequences are largely unknown.

To use a revolutionary comparison, who could have predicted that the storming of the Bastille prison in 1789 would lead to a little-known army officer, Napoleon Bonaparte, crowning himself Emperor of France in 1804?

From where we sit now, many questions about generative AI remain unanswered. Will storytellers and journalists become redundant? Can anyone trust an academic essay ever again?

As generative AI gathers pace, will that lead simultaneously to a progressive dumbing down of humanity as people outsource all tasks to AI?

According to a new report from Forrester, by January this year, ChatGPT had become the fastest-growing consumer software application in history.

It had “disrupted software roadmaps everywhere and began sprinting into businesses through four doors.”

The Forrester Report, titled Generative AI: What It Means For Content Management, looks at generative AI’s impact on content pipelines and how business leaders need to “weigh the benefits along with business context, risk appetite, and the maturity of their risk programs.”

Let’s get fast

One of the significant impacts of generative AI has been on speed. Once organizations manually created copies and generated product information. Now, this can be done and made ready for review within seconds.

Content can be translated at scale within minutes, and lengthy creative ideation cycles are superseded by multiple directions in creative design ideation within minutes.

Given these temptations, it is hardly surprising that—according to Forrester—62% of global business and technology professionals familiar with their organization’s tech strategies and priorities “say that their organization plans to significantly increase AI investment over the next 12 months.”

“Instead of hiring more copywriters, we are now hiring content aggregators to grow the business.”

“Our research, based on discussions with more than 25 business executives, data scientists, and content management team members, validates that the generative AI business case is grounded in time-based competition principles,” the report says.

"Making the organization's value-delivery systems more efficient and faster will allow the enterprise to gain a competitive advantage in the market while increasing variety and staying responsive to customers.

“The impacted cost drivers—increased employee productivity, brand consistency in market, and decreased time to market—aim to beat competitors in new customer acquisition, account/customer growth, and geographical expansion.”

Tone and voice

The report quotes some leading global examples.

Lloyds Banking Group in the U.K. uses Acrolinx to help derive the right tone and voice for 13 of its brands.

Chris Whitwam, senior product owner at Lloyds, shared: “We discuss tone and voice standards to teach the tool, such as using the word ‘select’ instead of ‘click’ and following overall design standards [in conjunction with tone and voice]. This is a new learning process for our teams, but they are getting used to managing the tool as it suggests alternatives [and helps reduce the risk of inconsistent content].”

Metro World News, a news organization based in Latin America, previously used Google Translate, which required content editors to take 20 to 25 minutes to resolve inaccurate translations and localization within the articles.

Using ChatGPT integrated into Arc XP’s CMS, it takes its teams only three to five minutes to review each translated story, and sometimes, a translation is perfect in the first pass from the machine. Vicente Yarad, head of business development at Metro World News, told Forrester: “We don’t know yet how it will impact revenue, but we are expecting a 20% to 25% increase. Instead of hiring more copywriters, we are now hiring content aggregators to grow the business—we plan to increase headcount.”

Risk framework

The report concludes with Forrester’s risk management framework for generative AI content implementations.

This balances the impetus for organizations to move at scale while Governments and regulators respond with their own risk frameworks.

“Global business leaders, stuck in the crosshairs, need to comprehensively evaluate the speed at which their organization should move from experimentation to implementation,” the report says.

“This requires leaders to navigate the known and emerging risks of generative AI by assessing three facets of their risk programs.”

These three facets balance business contexts, risk appetites and the maturity of the technology and their own readiness to implement.

From there, Forrester has constructed its risk appetite framework hierarchy, which it recommends organizations move through as they ponder generative AI and how best to use it.

Revolutions can have explosive short-term consequences, but history shows us they are part of an evolutionary process.

So, while generative AI might be the big story of the moment, those organizations that will succeed are the ones who play to "win the long game."

Lachlan Colquhoun is the Australia and New Zealand correspondent for CDOTrends and the NextGenConnectivity editor. He remains fascinated with how businesses reinvent themselves through digital technology to solve existing issues and change their business models. You can reach him at [email protected].

Image credit: iStockphoto/rudall30