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Who will emerge as the winners and losers of AI?

Who will emerge as the winners and losers of AI?

In the ever-evolving landscape of technology, the rise of artificial intelligence (AI) has become an undeniable force of change. Amidst the hype and speculation, one question stands out: who will emerge as winners and losers as AI adoption accelerates among consumers? While many uncertainties remain, it is increasingly clear that AI has the potential to revolutionise the way we interact with the digital world.

Ultimately, how we change the way we interact digitally, as a consequence of AI, will determine where investment fortunes will be made or lost.

At the core of AI transformation lies the question of whether AI will merely supplement our current online experiences or become integrated as autonomous ‘agents’ that anticipate our needs and act on our behalf throughout the day. The answer may lie in recent developments that showcase AI’s immense utility.

AI’s capabilities have already begun to shine, with evidence of its ability to outperform humans in various tasks. For instance, while Chat GPT 3 made a valiant effort at the U.S. multistate bar examination, it was GPT 4 that achieved an impressive 75 per cent score, surpassing the human student average mark of 65 per cent.

One event that sheds light on the potential of AI agents is Salesforce’s recent demonstration of its Einstein AI agent. Launched in 2016, Einstein has proven its capacity to enhance business functions such as sales and marketing, improve customer experiences, and boost productivity. From correcting customer classifications in customer relationship management (CRM) databases to autonomously composing personalised campaign emails, Einstein showcased AI’s transformative power.

The real disruption lies in the prospect of AI agents controlling the consumer journey. Just as Google has wielded significant influence over web browsing, AI agents could analyse consumer preferences, qualifications, and needs to guide them in various aspects of life, from job applications to shopping choices.

Consider the automation of the weekly grocery shop by AI. An agent would handle the entire process from selection to payment and delivery efficiently, reducing waste by buying only what the family consumes and saving costs by purchasing from the cheapest suppliers, all while accommodating individual preferences and needs.

Under this autonomous AI agent scenario, the dynamics of consumer engagement are set to change dramatically. Traditional influences like product images and advertising may no longer hold the same sway when AI is orchestrating the selection, ordering, payment, and delivery processes. The future of text or image-based searches also remains uncertain, which probably explains the driving force behind the massive investments made by tech giants like Microsoft, Google, Apple, and Meta in AI.

They recognise the potential to control traffic in a world where consumers increasingly rely on AI. For instance, in 2023, iPhone users accounted for approximately 18.55 per cent of all smartphone users worldwide, and Apple is expected to launch its first AI solution in 2024. The potential for Apple to supplant if not usurp Google in the consumer value journey is material.

While it’s still early days for AI adoption, the speed at which it’s growing is remarkable. In the case of ChatGPT, part of the first wave of AI, it amassed 100 million users in just 61 days.  This compares to Twitter, which took 1903 days to reach 100 million users, and Facebook’s 1608 days.

In this AI-driven future, consumer engagement with the internet is likely to increase, albeit through AI agents. As AI handles more tasks, users may spend less time individually online but generate more sessions through their agents. The economic implications of this shift are yet to be fully understood.

The impact of AI extends beyond consumer behaviour to businesses and investors. Business models will evolve through the next wave of creative destruction, and the value of consumer data will skyrocket. In a world with AI agents, lower-value goods and digital platforms may become commoditised.

As we contemplate the future, one thing is clear: the collision of AI, user engagement, and foundational technology is poised to bring about profound changes. As AI agents become more integrated into our lives, the way we engage with technology and the internet will continue to evolve, potentially reshaping industries and creating new opportunities for those who embrace this transformative wave of innovation.

The Polen Captial Global Growth Fund owns shares in Microsoft and Alphabet. This article was prepared 20 September 2023 with the information we have today, and our view may change. It does not constitute formal advice or professional investment advice. If you wish to trade in Microsoft and Alphabet, you should seek financial advice.


Roger Montgomery is the Founder and Chairman of Montgomery Investment Management. Roger has over three decades of experience in funds management and related activities, including equities analysis, equity and derivatives strategy, trading and stockbroking. Prior to establishing Montgomery, Roger held positions at Ord Minnett Jardine Fleming, BT (Australia) Limited and Merrill Lynch.

This post was contributed by a representative of Montgomery Investment Management Pty Limited (AFSL No. 354564). The principal purpose of this post is to provide factual information and not provide financial product advice. Additionally, the information provided is not intended to provide any recommendation or opinion about any financial product. Any commentary and statements of opinion however may contain general advice only that is prepared without taking into account your personal objectives, financial circumstances or needs. Because of this, before acting on any of the information provided, you should always consider its appropriateness in light of your personal objectives, financial circumstances and needs and should consider seeking independent advice from a financial advisor if necessary before making any decisions. This post specifically excludes personal advice.

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  1. Hi
    I intend to see if I can link an AI functional learner to some fundamental company data.
    Not expecting any success ; ‘current performance ‘is not an indicator of future performance.
    Do not have access to all data that can influence results (the white swan problem). Also functional learners can not in general learn any ‘relational’ interaction between the data. Also the ‘survivor bias’ problem. So should in general ‘fail’. However interesting. A while ago I tried to see if PEG etc could be a predictor for eps growth (a common approach which is simple functional learning application.) No link found- Unfortunately the actual data etc is important so failure NOT a guide for more complex trials. (certainly not sufficient to counter ‘believers’ .) I suspect that at least one (and probably another) ‘commercial’ company recommendation site use a complex ‘functional ‘ model. Unfortunately neither of two I have contacted is willing to admit the methodology,describe any validation; let alone, provide sufficient information, or data to test AI learners. (IP?? ) In some cases I would expect that AI could ‘do as well (not much worse than’ ) current forecasts. Neither being sufficient.
    PS Value.able value model is ‘functional’

    • Sounds fascinating. I’d be very interested in your results. Subscribing to the necessary data is expensive and the data isn’t 100% accurate. I should know, we subscribed to data for Skaffold from one of the major global providers and we had to employ our own people to ‘clean’ it. So even if you have the data it could be a case of ‘garbage in and garbage out’. BTW it all comes down to expectations. That is what you need your AI to solve for. The best performance, including rising intrinsic values, comes from companies that beat expectations.

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