Top 10 Emerging Technologies In 2023 | Forrester Podcast

foreign [Music] hi I'm Jennifer Isabella and I'm Stephen powers your co-host for Foresters podcasts what it means where we explore the latest market dynamics impacting Executives and their customers today we're joined by vice president of forester's emerging Tech portfolio Brian Hopkins and vice president and principal analyst Michelle Goetz to review our top emerging Technologies for 2023. welcome both all right thanks yeah thanks for having me so before we dig into any specific Technologies Brian I'd love to maybe just level set like how is this list organized how did you come to this top 10 list amongst other things maybe you could start there sure absolutely this year we evolved what we did last year to really try to organize the top 10 Technologies by an answer to what we think is the number one question our clients have is this technology ready for me what's it going to do can I use it and that's really not just a matter of the maturity of the technology but it's also a matter of the maturity of the organization considering using the technology so we call these three kind of time frames benefits Horizons and we have short bid and long term I think it's uh now to two years two to five years and five years out and when you look at those benefits Horizons what we're saying is that in the short term we think that these Technologies are going to deliver a really tangible Roi now over the next two years so it's really about that hard dollar return on investments for most firms the average firm will be able to get that Roi the midterm is two to five years and we think the language we use there is a significant benefit so it's not really Roi it's more like the average firm is going to see some really substantial things out of these but it's going to take a few more years and then the last one the long term what we say is expected value so it's a really squishy term and those things that are five years out who knows what's really going to happen in five years so again we're saying the average firm that's going to see something big but it's going to take a while and the last thing I'll say about potential Horizon is it's the average firm realizing that there are firms that are more advanced that take better risks on technology that invest more in technology and they're going to make faster progress than the average firm so the benefits Horizon is really kind of a fine nuanced way of organizing the 10 technologies that tries to answer that question based on kind of the average spur I will say that we landed on the 10 this year doing the same thing we did last year we start I have a database that I developed got about 400 Technologies in it this year we add all the techs in our Tech Tides we add Technologies I get talked to a lot of clients and we went through a process of screening that 400 down to 75 that we call Priority and then from that 75 we did a lot we ran a survey of analysts we looked at a bunch of data we looked at documents and readership and we looked at external data sources and we went through a whole kind of rigorous process in several rounds of collaboration to get down to 20 and then from that 20 we kind of strategically talk to our leadership and talk to some senior analysts and align those 20 to what we thought the most important things for businesses were going to be and that's how we got to the tin the benefit Horizon concept is really interesting to me and obviously it depends on the technology but are there characteristics of certain firms which will have a faster benefit Horizon well the benefit Horizon is actually assigned to the technology and the characteristics of firms that are going to move faster on Technologies and therefore get faster benefits we align those carefully to our customer obsessed maturity model and our itany maturity model which kind of when you look at those really you have two sides of the same coin and so if you look at our I.T maturity model we categorize the more advanced firms is kind of modern and there's like 32 percent of firms are moderate and about eight percent of firms are what we call Future fit and those future fit firms and the modern firms that mostly it's the future firms that our data tell us are moving a lot faster on emerging Technologies they're able to take better risks and therefore are going to get much more benefit from these emerging Technologies than come in the middle of the bill curve firms so it's it's that future fit it has to do with being adaptive having a lot of resilience in your your infrastructure having a lot of creativity in the way that you apply the use of technology for Innovation so adaptive creative and resilient that's really the elements of future fit so we should move on to the actual top 10. everybody's talking about gen AI you know it's number one why that's a great question well obviously it's what everybody's talking about right now and the reason why it's number one is because it's so foundational to many of our other top merging Technologies uh conversational AI is certainly being driven forward by generative AI autonomous workplace assistants which are kind of the back office employee supporting and process automation tools are also being driven by generative AI things like touring Bots automated code generation Bots are being driven by generative AI so when you look at the kind of astounding capabilities of generative AI that anybody can go look at and play with these open source and publicly available tools it's hard to imagine engagement or a process that can't be rethought using some flavor of that technology and then that's going to accelerate so many other things so it's really hard to say that that's not the number one thing but it also comes with a ton of risk right and that's a lot of things you're grappling with right now those risks a little bit yeah absolutely so there's a number of risks associated with generative AI I'll hit on them real quickly but I want to spend some time asking Michelle to kind of reiterate what she told me because I was like wow that's cool but primarily you know there's the risk of hallucinations right these things think they're right and they're not and it's hard to tell you know it was listing the CEO of Google who's Frank he said we don't know that this is actually something we can solve but you know how do you trust these things that's the big thing right how do you trust them what's the evolving regulatory environment look like I mean if you look at the stuff that's going on in Europe right now with the AI act and they're a requirement to register all these and test all these AIS before you can really use them the third thing is IP right you have to register in the European AI act you have to register all the source data that you use to train your AI especially if that data was copyright and that's what we're seeing is we're seeing these tools learn from all this stuff that's out on the web but it's copyrighted now like if I trained my AI on your stuff you bio your royalty if I make money and that's creating this idea of a lot of what we think is going to be these Royal Gardens that are making that data available on the web oh no no no if you train your AI I want a piece of the action I wanted a shelter kind of jump in there and tell us what she was saying yeah so you know with generative Ai and particularly as we've seen with chat GPT anybody and everybody can bring their own AI to whatever use case they want it's not just in the hands of Enterprises anymore and so many who are data Savvy or they're Savvy with their business applications they know how to extract as much information or content out of those environments as they need to to do their jobs or to extend the types of value or objectives and goals that they're going to have now that's sort of this internal play and organizations have gotten pretty Savvy up from a data governance perspective on how do you create you know stronger access controls observe the types of information that you know different employees are using so that the data security internally is evolving and working quite well the challenge also comes into play though is as you start to allow this to flourish Within in any type of person can work with it my 80 year old mother can talk through chat GPT and get answers on her own so she can do it imagine what you're you know 20 something as an employee is doing now but what does this mean it means that all information that's available is up for grabs at this point if you can you know click into a rest API and move it into your own generative AI function well now you're going to bring in content you're going to bring in chat messages you're going to bring in people's digital asset that they've created as well and I think what you're starting to find is first it was the conversation with technology firms or firms that are driven by technology like big Financial Services organizations where they're saying from a engineering perspective you are not going to use any of these generative AI capabilities to help create code for our systems because accidentally our our IP can get out there so that's the first Walled Garden is you can't even apply this on your own information but the second thing that's starting to happen is you see this within some of the social media areas if you look at Twitter you know they're changing their subscription models that's you know costing you to access information they're restricting how many tweets can come down and you can use that to train the system if you take a look at the snowflake Marketplace environment you're having to build these apps to access information but they're going through subscriptions you have contracts around these things and I think at the end of the day General AI is only as good as the information that you're going to provide that and for those who control the information that can really improve and make it better and take generative AI to that competitive Advantage they're finding ways to up the value of the data so it's not just how effective or how much should I charge search for the algorithm it's now how much of a premium do I charge on my data and so this is that notion of that wall Gardens that I think we're going to see start cropping up Michelle do you think that for the average firm their governance is keeping up with the velocity of the technology not at all most people in an organization can do a download of all of the contact information from Salesforce through you know a easy export function or a report export you can go into your SharePoint environments and you can download all of that content we all have different Rights Management to help us do our job but we haven't been thinking about how do you take that information and feed that into an AI system the AI of the past was part of the technology the hardcore or citizen data scientists who knew how to use these tools now that it's accessible to everybody that's just a use case that we haven't thought of and we also don't know what generative AI tool is being brought to bear in the organization so you don't know how that tool was trained you don't know if it's coming from a reputable Source you don't know if it's introducing its own malicious you know malware code data into your own environment and we don't have strong enough observability to see what tools today are being used not just from a data perspective but even from an AI perspective so I think that that's really where cios are kind of struggling because they know Pandora's Box is open already everybody's using it so now they're trying to figure out like well how do we build the right literacy around it so that we protect ourselves yeah it's interesting it's one of the things I hear when I talk to folks about it it's like this is advancing at a speed that we didn't expect that we can't deal with and it's one of those things where you know Michelle we've been working together for years I've been writing about this whole kind of the exponential power for servers led to Cloud accelerated Big Data Big Data accelerated machine learning massive compute on top of machine learning created better deep learning deep learning now led to generative Ai and one after the other in this that acceleration of benefit means that you know unless you've taken some steps up until now to really be future fit you're going to struggle with all of these Technologies and generative AI is just it's fun to talk about it's everyone's talking about it but it's just kind of the tip of the iceberg right and that's kind of why it's back to your question why why it's number one I was just going to ask if there's a connection between the comment around like walled Gardens as you had mentioned Michelle and the industries that we think will benefit the most from generative AI or is there really no connection there so let's think about companies that have been producing content for quite some time I mean it's no surprise that media companies are interested in how do they take their scripts how do they take their digital assets how do they start you know morphing those they've been using AI for quite some time to generate movies we've all seen avatar for example we see all these great effects on things like Maverick and Top Gun but it's like now you can do all of that on steroids so instead of creating and editing a film that takes the years you can start shrinking that down and have more granularity in other players involved in crafting that versus just a digital artist for example so media is one of those areas social media is a Bastion for content and while they may be walling their world off from us and constraining what we have access to you gotta know that they're exploiting that information in some manner shape or form and while it could be an advertisement venue I think that there's gonna find find that there's other types of products and services of value that can come out of you know stronger Mining and using of this information through generative AI functions but even within um where the engineering types of organizations and and industries I mean you're seeing generative AI used in simulations to craft like you know class you know sailing boats to you know sail in the world in the in the US cups and so at that point you know they're able to design a whole sailboat without ever putting something together physically and throwing it in the water and now they're saving millions of dollars and they can do that you know redesign that year upon year upon year take that to Automotive take that to other Transportation so you see how this is evolving to lead in other areas and at the end of a day maybe there's more applications that are being distributed out from companies like a Salesforce like a servicenow like a work day that are gravitating towards all the content that they've been collecting and helping us to better train our employees to give us new apps to do our jobs better and so I don't think that there's actually going to be one industry that benefits the most but certainly those that have the Walled Garden today are in a much better position if they've got their data house in order so what else is in the most immediate or short-term bucket in terms of our top 10 list and why it's really funny because the other two are actually there being accelerated by generative AI so it's really kind of a threesome it hits our short-term bucket right so the other two are conversational Ai and autonomous workplace assistance when we kind of talk about each for a sec we differentiate between conversational Ai and generative AI as talk most people know gender of ai's got a lot of use cases in imagery and computer vision and other places but when you think about what tools like chat GPT are doing is they're taking a generative AI model and applying it specifically to a natural language conversation so we talk about conversational AIS as kind of the manifestation of the next generation tools that we used to call them chat Bots right but we all know that a chat bot today if you've ever experienced one is not at all helpful for most companies that you work with they're very rule-based they're very heuristic and they often miss the mark but they're getting a lot better and so what and they've been on many of these chatbot tools have been all over the market now for you know at least five years so what we expect to see over the next two to four years is these tools really accelerated by the capabilities that reinforcement learning large language models transform our networks and all the pieces of generative AI really bring to those conversational interfaces and so we think that the time of the conversation AI is really going to begin donning over the next couple years autonomous workplace assistance last year we call these things intelligent agents but what we found in talking to clients is that word is a little nebulous and so the research analyst who works in this area Greg LeClaire renamed it awas or autonomous workplace assistance to really focus these things on software robots that help automate back office processes to make them more efficient and focus on employee facing software robots that really represent the intersection of yesterday's RPA or BPM software packages those things are kind of coming together and they're becoming infused with conversational interfaces to support for example call centers maybe to summarize or anticipate what are calling client wants or needs as well as being infused with other kinds of more basic Ai and capabilities like text analytics entity recognition models and so on and so forth so these autonomics workplace assistants are really kind of the back end bot and conversational AIS are showing up first is natural language interfaces to chat Bots for example but they're also then conversational AIS are showing up as components of these automated workplace assistants which are focusing on employees and back office processes so you really have these kind of three major AI autonomous workplace assistance and conversational AIS all working together to create a lot of very rapid benefit for front and back office and that's like it's creating a pace that our clients have really never seen before but we've been seeing that train coming for a number of years and now it's about to run over us so that's what's really right into one of those clients at least that's what we found in our report let's maybe move on to the the medium term which I think has four Technologies in it right let me just hit a few first and say the ones that were on our list last year that made it this year again are explainable AI which is kind of medium term last year and it's a medium term this year think about this right if AI is about to run over us and the age of AI is Dawning or whatever you want to call it the one thing that clients really need to take advantage of that is you got to be able to trust what these things are doing and trustworthiness is probably the number one issue is how do you believe how do you know what this model did how are you going to put this thing in front of your customers an explainable AI attempts to do that the problem with explainable AI today is that it's a separate set of skills and tools from the places where you actually might interact with for instance a bot so bringing those two together and infusing the user tools the call center software that now has a generative AI capability built in or your sales force now as generative AI summarizations of the last conversations with a customer how do you know what that thing's telling you is true you need explainable AI capabilities in those tools so business people can become more comfortable and that's going to take a couple more years but it's really really really important the other one that was in our list last year other two were decentralized digital identity that's kind of a new one this year and essentially what decentralized digital identity is saying is that all the things that we use like driver's license or identity cards all the things that businesses use to understand who you are and for a financial services referring to for instance know your customer to do that check-in are you who he thinks you are so we can trust you and do business and and let you do business with our partners all that's very centralized today uh and it's centralized with whatever business happens to be doing it in that that interaction of me knowing who you are so I can work with you has to be repeated for every every time a customer goes somewhere else and decentralized digital identity takes blockchain and it takes things like zero knowledge proofs and it says we can create a decentralized infrastructure so that within an ecosystem of Partners who are all cooperating on the blockchain we can establish trust relationships so that a trust relationship between a consumer and a company a can now be moved over to that same consumer with Company B and it's much more frictionless and at the same time you can protect that consumer's actual information so that the consumer's privacy is preserved so it's kind of a privacy preserving technology but it's a scale technology in terms of scaling identity and access management it's been around for a while it's not new but it's moving very slowly because of the standards required to adopt this thing are not yet mature yet there's capabilities like transitive trusts that are needed there's some ISO standards that need to be implemented by the vendors it's just because it's about adoption and standards and it's about people businesses finding win-win that's moving very slowly last thing I'll say quickly is about turning box and that's really being accelerated by generative AI if you look at things like Microsoft co-pilot if you look at some of the capabilities in Google today where they have a whole code generation module we looked at these things and we called them touring bots in 2020 we said hey these are coming and everyone kind of looked at us like what the heck are you talking about Flash Forward three years and these things are just all over us and they're making software encoding artifacts all across the software development website cycle and this is only going to accelerate I want to spend a minute and ask a little bit about Edge intelligence which is something that I kind of worked out some research a while back but I know that Michelle has been doing a lot around that well I think the thing is first like you and Michelle Paulino put in some really groundbreaking research around Edge Computing which sort of redefined and recast how we think about Edge from not just being about iot but really thinking about the edge of value where you're actually delivering on what businesses are trying to achieve or how you're actually operating at the core and so I think that first took a little bit for people to get their arms around and recognize like oh I'm not thinking technology I'm thinking about what am I giving as a return on investment and then but now that we Infuse intelligence into that it's like well now we're thinking about the use cases we're thinking about what the compute is actually doing it's processing information that's processing different types of experiences and then it's process accessing the Intelligence on top of that and I think what's really great right now and while it still makes the list rather than falling off is that organizations really needed to build a data Foundation of essentially you know data pipelines a network of information in and out and Beyond the um you know the organization and so they've spent a lot of time effort and investment in doing stronger adoption of event-driven architectures um it you know taking on and adopting streaming data platforms and getting familiar with these and more simplistic use cases of just being able to transition information to be able to be effective in automating a process or delivering an experience or transacting you know in a retailer Commerce setting now it's like we got to put the AI inside it um it's not easy to deploy AI models because there's again models even with generative AI it's usually a collection so you have to really think about what is the ontology of that AI architecture you have to think about where all of the you know aware and how all of these models are going to speak to each other not everything's going to come back to the cloud anymore and process sexually it's also going to process on the edge and we're still evolving The Edge data management capabilities and you know both locally in our Edge servers but also out on our devices and so that has to work and then once you start thinking about that and you're adding more value and you're also adding more risk as AI goes out especially if it's generative AI security matters privacy matters and the security and privacy control plane has not quite caught up yet to where we need to go so similar to what you were talking about of decentralized digital identity that's another facet that needs to further evolve intelligence is somewhat different than some of the others on the list because it's really much more of a holistic solution and platform it's relying on a multitude of existing Technologies and other emerging technologies that actually get to the end state but it's moving quickly and organizations are definitely on the right adoption path so it's not that it's stalled so much it's they're learning how to put the pieces in place let's talk about some of the remaining texts that we have on our list particularly the ones that aren't going to deliver value for five or more years but what are those texts and why aren't they going to deliver value for a little while longer yeah well I the three that are on our list for kind of five years plus or extended reality which is on the list last year web tree which is on the list last year and zero trust Edge and if we look at each one of those the stories are a little bit different extended reality really there's two sides of that story there's a consumer Story and there's a B2B or a business 2 Enterprise type of story first off let's say when we stock or talk about extended reality we're really using an umbrella term to mean augmented reality virtual reality mixed reality we're kind of what we see is a fusion of those Technologies into what we're calling extended reality and the Enterprise uses of those Technologies are really moving a lot faster than the Consumer uh our data tells us that on the consumer side adoption just isn't there the foreign Factor needs more time to get smaller to get more affordable and for people for consumers really Minds to change because what we've seen is we as consumers I've done this as well we become very good at being trained over the last 20 years to use The Mouse and the screen and so getting away from Mouse and screen is going to maybe even take some generations of people who just they're used to using more of a uh of a visual interface and you know changing the interface can change the world but it's gonna take time in the meantime we're going to see some employee facing use cases specifically and onboarding and training those are the big things right now and we're going to see you know collaboration kind of behind that so the employee facing uses are going to lead the way ahead of consumer-facing use cases that consumer adoptions just going to take a while to happen as we think it is going to happen it's going to be a big piece of something we call anticipatory experiences but it's going to take a while zero trust Edge is another one we just think needs some time the whole idea in zero trust edges that it's really a piece of that edge story that Michelle was starting to tell well one of the issues that we've we've been writing about this for years this whole idea of a zero trust architecture and a zero trust security architecture means trust nothing inspect everything that's the way I think about it and to do that you have to look at every packet of information flowing across your networks and various Network topologies and configurations depending on what you're trying to do and you know is it a streaming kind of Architecture is there real time is it you're moving everything back to the cloud are you doing your analytics in the cloud your network needs to change based on on your needs and software defined networking is a great solution it's been around for a long time it allows you to reconfigure via software the kind of network you need to meet a particular use case the problem and now what we're starting to see is these software-defined networking networks implementing the zero trust security model cool the question is and if you have all these software-defined networks out at the edge in many different remote sites many retail sites or offices or manufacturing plants or wherever Smart Homes or wherever how do you control all the separate Network configurations that are in different places and the answer is you centralize a control plane in the cloud so what we've seen is security vendors by networking vendors networking vendors buying security vendors and everyone's trying to figure out how to create this one package to rule them all to manage both the network the security and the control and how do you do it and that's going to take time to work through these Acquisitions so those two XR and ZTE we think are definitely right in front of you but it's going to take time to get there five or more years Webster is a different Beast the promise of web 3 is this Democratic internet right the Democratic token based take control of your data control your life participate in the ecosystem it's all open source it's all via tokenomics and cryptocurrency that sounds great and it was really exciting last year because it got wrapped up in the whole metaverse thing the issue that we're seeing is this is still basically a self-referential group of people who are focused on financial engineering trading and applications built on top of cryptocurrency and we don't see very many indications that it's going to move beyond that and that whole area is fraught with risk and Scandal and I'll tell you a lot of most firms haven't really figured out what their position their real position on accepting cryptocurrency is going to be and that is going to take a while so we just don't see a lot of evidence that web3 is going to move very quickly to that thing that's being promoted and we think that even when it does it may not be called web3 anymore so we're pretty skeptical on web3 whereas the other two we know they're coming they're just taking longer because of all the dependencies we've discussed so Brian when you were introducing this list you were talking about oh we have a list of hundreds of technologies that we pair down to 20 and then we debate them and we get input from a variety of sources so maybe share a little bit not that these are on The Cutting Room floor by any stretch because we talk about probably these other Technologies quite a bit but which of the Technologies were hotly debated almost made the list but maybe didn't this year there was also another debate that we had about even how they got onto the lists too which was the technology knew or was the application of that technology new that was an interesting conversation oh it totally was Michelle that and what actually happened is there's a number of Technologies I think there were 18 of like low code platforms or something I still see on people's technology watch list today iot platforms is another one that we think those are actually from a technology capability emerged so we created this emerged group and there's a group of really important technologies that get out of the market for a while so the capabilities are mature but they still haven't necessarily reached equilibrium in all the Industries or with every firm that needs to so those there's a lot of news that we decided to say that were emerged and we kind of excluded them from our listing they're really important Cloud native Computing which is on our top ten last year moved off our top ten and now we think it's emerged it's like we think that's really important to your core competitive Advantage if you aren't all over it you should be so that's a good reminder Michelle about that just to answer your question though what were some things we debated I think one of the hot things of course we debated metaverse I think the metaverse winter that we're seeing right now that we call last year in our research right before it happened is I don't know I'm going to Pat myself on the head or pout us on the head and say you know we didn't have metaverse on our top 10 last year even though we could have put it there because it was all the rage we also saw some of the weaknesses and actually what is this thing and and is it going to persist in our and we made the call that we thought that it might not by not putting it on the top ten this year a lot last year and we didn't put on the top 10 this year even though it's in our next 20 specifically so we can have the conversation about you know what happened why another one that was debated is this whole idea of where Quantum Computing fits um we seem to be pretty close to some real Advantage uh we're not there yet but close to some real Advantage with certain kinds of problem computers for something called noisy intermediate scale Quantum Computing applications or disk but we're still not quite very at and we think that they're still going to be a fair amount of time before maybe five plus years or longer will really begin to see the average firm be in a position to do something useful with quantum computers but we really looked at it hard the area where we really thought was interesting is in Quantum security I did an analysis with our security team about the amount of time it might be before quantum computers could in Theory start decrypting pki encryption and I think the number we came up with is about most likely 13 years from now 13 was about the number we came we see a small probability maybe 10 to 12 percent chance that it will happen much faster perhaps even within the next five years so if you really want to be cautious about your information anything you're sending across the wire needs to begin to migrate to Quantum safe encryption now on that small probability that in the future within the next few years that information will be susceptible to being hacked if it's encrypted in asymmetric key encryption so those were some things that we really debated about but they didn't quite make our top 10.

exciting stuff um really excited excited here and go deeper a bit more bit more at our technology and Innovation events coming up later this year thank you both Brian and Michelle for joining us today thank you both thanks for having me yes absolutely thanks for having me if you like what you heard today please be sure to check out our upcoming technology forums starting in September to learn more visit four.com Tech events that's for.com slash Tech events thanks for listening [Music]

2023-08-01 22:36

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