How 10X AI Value Is Reshaping Tech Adoption
For decades, the Rogers adoption curve has helped explain how innovations, from electricity to cloud computing, gain traction over time. Adoption typically followed a steady pattern from innovators to laggards, but today, AI is disrupting that pattern.
According to a March 2025 McKinsey report, over three-quarters of responding organizations reported using AI in at least one business function, up from 55% in 2023. The pace of adoption has accelerated faster than any prior enterprise technology.
Industries like media, which traditionally fell into the late majority, are now demonstrating early adopter behavior. Once-cautious players are accelerating adoption timelines due to economic necessity and strategic urgency.
Why did the traditional adoption curve collapse? The 10X effect.
What's changed? The simplest answer is the value multiple. In the past, new technologies might have offered a 2X return, enough for a pilot but not enough to force action. AI, by contrast, is delivering 10X or even 100X improvements in efficiency, time-to-insight or cost reduction.
That level of value is shifting how adoption timelines are understood, accelerating what used to unfold over years into changes that now happen within quarters. On the Rogers adoption curve, shifts from laggards to early adopters once took decades. Now, they happen in quarters. Organizations aren't necessarily becoming more risk-tolerant; economic pressure is compressing their shift within the adoption curve.
The Rogers curve wasn't built for step-change innovation.
Rogers' model was grounded in psychology. It is assumed that adoption would follow individuals' risk tolerance. New technology, lacking a proven track record, naturally attracted those willing to take a leap. However, AI is changing how risk itself is evaluated. For many leaders, urgency is now a stronger driver of technology decisions than traditional risk tolerance.
When tools can automate hours of manual work, optimize marketing spend in real time or streamline customer support, the conversation shifts from "should we?" to "can we afford not to?" In September 2024, a Gartner, Inc. report found that 44% of finance functions used intelligent automation and 39% use AI for anomaly detection. Sectors like legacy media, automotive retail and property management have also begun moving aggressively. For all, behavior isn't the core driver of change; the stakes are.
10X value is forcing strategic realignment.
Any IT leader knows that most technology decisions aim to cut costs, increase efficiency or reduce risk. Often, that means choosing tools with marginal returns. Upgrading a chat app or project tracker helps workflow but rarely moves the needle.
AI is different. It's driving exponential gains in creative production, analytics and customer service. An October 2023 Gartner survey found that 45% of responding enterprises were already scaling GenAI across functions. These gains are driving real-time change.
As performance gaps widen, laggards are being pulled forward. Competitive pressure is accelerating adoption as companies respond to tangible performance gaps. AI may not solve every challenge, but it acts as a force multiplier when applied to the right workflows. Smaller, more agile firms are now using it to challenge incumbents, rewriting the balance of power in entire sectors.
Unlike legacy systems that required expensive integrations, AI scales with data maturity and model access. As a result, even firms that typically watched and waited are finding it riskier to sit still. Rogers' model once gave laggards the benefit of learning from others. Now, delaying evaluation too long may result in missed opportunities to shape adoption on your terms.
Many companies are adjusting in real time. A May 2024 Forrester survey found that 67% of responding AI decision makers had planned to increase investment within a year. That momentum has made AI benchmarking an active and ongoing part of competitive strategy, further backing the idea that change across sectors of the Rogers curve is happening in a much more compressed fashion.
It's time to reevaluate your tech adoption strategy.
Fortune cited a March 2025 Dataiku report that found that nearly three-quarters of surveyed CEOs feared losing their jobs if AI investments didn't deliver results within two years. That level of concern signals to IT and business leaders that the adoption model must evolve.
This is a chance for IT leaders to guide their organizations by clarifying where AI fits and where it doesn't, so that adoption moves from reaction to readiness. A good starting point is examining how Frankenstacks formed. The Rogers curve wasn't designed as a diagnostic tool, but it can serve as one. Understanding where your organization typically falls can inform how you approach AI and future technologies.
If AI is expected to be a differentiator in the next 12 to 18 months, early adoption may be essential. Teams that have succeeded by adopting later and integrating well can continue to perform if they stay aware of faster-moving competitors. This is the time to assess your position and identify areas for improvement.
To evaluate your position, consider:
• Are competitors operationalizing AI to drive outcomes? How do we define operationalizing AI in our context? What do we consider a measurable outcome?
• How are industry leaders integrating AI into strategy? Are their approaches replicable or relevant for our structure? Could AI help us improve outcomes differently from competitors?
• Are employees using AI tools with structure, or is usage ad hoc? Have we formally assessed internal AI usage? Are teams eager or hesitant to adopt new tools?
We need to reframe the adoption decision.
AI is becoming embedded in core business functions. Leaders who dismiss it may miss out on advantages already being realized. Gartner found that 78% of responding executives believed the benefits of GenAI outweigh the risks, and a SiliconANGLE report stated that 97% of leading adopters were seeing measurable gains.
However, speed alone is not a strategy. Action without alignment creates risk. The Rogers adoption curve can serve as a useful lens for self-assessment. Understanding your organization's place on that curve, along with its readiness to support new capabilities, can guide more intentional decisions.
Business use cases for AI continue to grow. The opportunity is clear, but risk evaluation is still essential. In an environment where 10X outcomes are possible, the next move doesn't need to be immediate—but it does need to be deliberate.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
16 minutes ago
- Yahoo
'This bull market in equities has a serious problem': Strategist warns a crucial AI-stock index is sending a potential bubble signal
The AI trade may be fueling a stock-market bubble, warns Sevens Report Research's Tom Essaye. Semiconductor stocks' performance is lagging, raising concerns about the AI-driven market rally. Plus, bubbles tend to form late-cycle, Essaye said, and the US economic outlook is weakening. It's one of the biggest mysteries in markets right now: Is the AI trade driving a stock-market bubble? While earnings remain impressively strong, the potential warning signs of a bubble are there. The S&P 500 is sitting near all-time highs after a 28% rally since early April and 57% gains since ChatGPT was announced in November 2022. Meme stocks are ripping, suggesting investor sentiment is abnormally elevated. Excitement around AI has also driven up market valuations to levels consistent with prior major bubbles, like those seen in 1929 and 2000. Tom Essaye, the founder of Sevens Report whose clients include advisors at some of Wall Street's biggest firms, recently addressed the topic in a couple of client notes. "Every bubble in modern market history has been based on a narrative, whether it be the internet or real estate. Critically, that given narrative is widely perceived by the investment world to be a source of unlimited earnings growth across most market sectors," he wrote in an August 1 note. "Today, that potentially bubble-inflating theme is unquestionably AI technology." As Essaye sees it, the best way to measure the health of the AI trade is to look at how semiconductor stocks overall are behaving, as chips are the lifeblood of AI technology. One can do this using the PHLX Semiconductor Index (SOX), a group of 30 stocks, he said. Comparing the index's performance to the S&P 500 over the last couple of years shows "this bull market in equities has a serious problem," he said. The concern for Essaye is that SOX still sits below its July 2024 highs while the S&P 500 has risen by almost 14% over that time. This suggests the market's rally, which is largely being fueled by the AI narrative, could be in an unhealthy place if many AI stocks themselves are failing to keep up their momentum. "The takeaway here is that if AI remains the primary source of bullish optimism for a continued rally in the broader stock market in the months and quarters ahead, this market is in trouble and at risk of rolling over sooner than later as the SOX should still be leading the market higher like it was in 2024, not lagging considerably over the last 12 months," he wrote. "That divergence in index performance is meaningful, and if we see the SOX roll over in the weeks or months ahead and start selling off materially, the S&P 500 will almost certainly not be far behind." Here's the performance of an ETF that tracks the SOX index over the last three years: And the S&P 500's performance: Another sign of a potential bubble, and perhaps of trouble ahead for stocks, is that the US economic outlook appears to be weakening, Essaye said. Bubbles usually form late in an economic cycle, Essaye said, and a recession usually causes them to burst. Job gains over the last few months have been poor, as payrolls data released on August 1 showed, raising recession fears. Plus, continuing jobless claims are creeping up, he said. Essaye wrote in an August 8 note that "it is critical to keep close tabs on economic data right now," adding that "stretched valuations in the wake of the S&P 500's rapid ~85% trough-to-peak rally since the October 2022 lows were established leaves the broader equity market vulnerable to considerable downside in the quarters ahead, pending economic resilience." Read the original article on Business Insider Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
16 minutes ago
- Yahoo
IPO market 101: Everything you need to know
Yahoo Finance Markets and Data Editor Jared Blikre, who also hosts Yahoo Finance's Stocks in Translation podcast, explains everything you need to know about the initial public offering (IPO) market. Catch more Stocks in Translation, with new episodes every Tuesday and Thursday. To watch more expert insights and analysis on the latest market action, check out more Market Catalysts. Related videos Labour's plans to tax people's savings accounts explained Waiter brings legal action against the Ivy over share of tips and service charge Up 33% in a year and still yielding 7.5%! Is this FTSE 250 dividend growth stock a screaming buy? 2 shares I'm keen to buy if they become cheap enough Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
16 minutes ago
- Yahoo
Cathie Wood Goes Bargain Hunting. 1 Dirt Cheap Artificial Intelligence (AI) Stock With Monster Potential She Just Bought
Key Points Cathie Wood is known for making high-conviction bets on speculative stocks. Wood recently scooped up shares of Alphabet, despite a bearish narrative surrounding the company's ambitions in artificial intelligence (AI). A close look at Alphabet's financial picture suggests the company's AI pursuits are paying off in spades. 10 stocks we like better than Alphabet › Cathie Wood has earned a reputation on Wall Street for making high-conviction bets on emerging businesses seeking to disrupt legacy incumbents across industries such as technology, financial services, and pharmaceuticals. With that said, every now and again, Wood complements some of the more speculative positions in Ark's portfolio with well-established blue chip opportunities. When it comes to artificial intelligence (AI) stocks, it should come as no surprise that Ark's portfolio includes several high-flying growth stocks such as Palantir Technologies, CrowdStrike, and CoreWeave. Also in the mix, however, are several members of the "Magnificent Seven." In late July, Ark added to an existing position in Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG) -- scooping up 181,640 shares in the ARK Next Generation Internet ETF. Let's explore how Alphabet is investing in AI to transform its business. From there, I'll break down some financial and valuation trends to help illustrate why Alphabet stock looks like a no-brainer right now. Alphabet's business is in great shape Alphabet recently reported operating results for its second quarter, which ended June 30. The company's largest source of revenue -- advertising -- generated $71.3 billion in revenue, growing by 10% year over year. Advertising growth from Google Search and YouTube was even more robust, coming in at 12% and 13%, respectively. Over the last few years, skeptics on Wall Street have been parroting a bearish narrative that the rise of ChatGPT and other competing large language models (LLMs) will diminish Google's dominance in search. Accelerating growth between Google Search and YouTube suggests that advertisers still see a high return on investment (ROI) from these platforms, despite some shifts in how people are consuming content on the internet. Where investors may be getting nitpicky is around Alphabet's profit margin profile. The advertising segment sits under a larger category of Alphabet's business, called Google Services. During the second quarter, Google Services grew its revenue 12% year over year to $82.5 billion. However, the operating margin for the Services business remained flat year over year -- coming in at 40%. When expenses grow in line with revenue, profit margins become capped. On the surface, this may look like Alphabet is not running an efficient business despite an accelerating top line. I wouldn't rush to such a conclusion, though. Over the last few years, Alphabet has made a number of strategic investments to bolster its AI position. For starters, the company augmented its cloud infrastructure business by acquiring cybersecurity start-up, Wiz, for a reported $32 billion. On top of that, Alphabet's multibillion-dollar investments in AI data centers are often underappreciated -- and yet it's this infrastructure that attracted OpenAI, a perceived rival, as one of Google Cloud's new major partners. Lastly, Alphabet is also quietly building its own quantum computing operation through the development of its own custom chipsets, called Willow. Although monetizing quantum computing applications is still likely many years away, I find it encouraging that Alphabet is allocating capital across several pockets of the AI realm in an effort to build a diversified ecosystem that strengthens core businesses while opening the door to new opportunities as well. Is Alphabet stock a buy right now? The chart below benchmarks Alphabet against many of its big tech peers on a price-to-earnings (P/E) basis. Ultimately, I think Alphabet stock is being punished by investors because the company isn't posting growth as robust as some of its peers. In my eyes, the fact that the company continues to grow revenue from its core businesses while striking lucrative deals with rivals and maintaining its profit margin profile in the face of aggressive investments shows a high degree of resiliency from Alphabet. Given the disparity in valuation multiples illustrated above, I think that the bearish narrative appears to be fully baked into Alphabet stock at this point. To me, Alphabet is positioned for significant valuation expansion in the coming years as its infrastructure investments continue to bear fruit. I think Wood identified a rare opportunity among major AI players by identifying such a cheap stock floating around in a sea of frothy valuations. I see Alphabet stock as a no-brainer buying opportunity at its current price point for long-term investors. Should you invest $1,000 in Alphabet right now? Before you buy stock in Alphabet, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and Alphabet wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $653,427!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $1,119,863!* Now, it's worth noting Stock Advisor's total average return is 1,060% — a market-crushing outperformance compared to 182% for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of August 4, 2025 Adam Spatacco has positions in Alphabet, Amazon, Apple, Microsoft, Nvidia, and Palantir Technologies. The Motley Fool has positions in and recommends Alphabet, Amazon, Apple, CrowdStrike, Microsoft, Nvidia, Oracle, and Palantir Technologies. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy. Cathie Wood Goes Bargain Hunting. 1 Dirt Cheap Artificial Intelligence (AI) Stock With Monster Potential She Just Bought was originally published by The Motley Fool Sign in to access your portfolio
