In the ever-evolving landscape of sales, technology has become an indispensable ally. Artificial Intelligence (AI), in particular, has emerged as a powerful tool that can revolutionize the way sales teams operate. For Sales Enablement Leaders, harnessing the potential of AI is no longer an option but a necessity. In this blog post, we will delve into the major themes that sales teams must comprehend before selling AI solutions to clients and prospects. We’ll also explore the criticality of having a sales enablement strategy that includes research-based tools.

Understanding the AI Landscape

Before diving into selling AI to clients and prospects, it’s imperative for Sales Enablement Leaders to have a solid grasp of the AI landscape. This involves understanding the core technologies of AI, the applications, and the capabilities brought to the table.

The Core Generative AI Technologies

The focal point of this AI innovation revolves around generative foundational models, with large language models (LLMs) being a notable component. LLMs have the capacity to be trained using exceptionally vast datasets and can generate fresh content (i.e., text, images, videos) by drawing upon previously created data, when prompted. Exploring the vital ‘sub-paths’ of integrating these models into custom applications, generic enterprise software, and other software development platforms is essential to fully grasp their potential impact.

Building Trust With Clients

The successful adoption of AI in sales hinges on trust. Sales Enablement Leaders must address client and prospect concerns regarding AI, especially those related to data privacy, ethics, and the potential impact on their business.

…the ambiguities over the authorship and copyright of AI-generated content are creating question marks around intellectual property management and ownership. All these risks need to be incorporated into a well-orchestrated trust and oversight program to ensure that these technologies can be deployed in a sustainable manner.

Philip Carter – Group Vice President, Worldwide Thought Leadership Research

Transparency: Transparency is key in building trust. Sales teams should be able to explain how AI operates, what data is used, and how decisions are made. Clients and prospects need to know that AI isn’t a “black box.”

Data Security: Assure clients that their data will be handled with the utmost care. Explain the security measures in place to protect sensitive information and adhere to relevant regulations (e.g., CASL, GDPR).

Ethical Considerations: Discuss the ethical implications of AI in sales. Make sure your AI tools adhere to ethical guidelines and do not engage in discriminatory practices.

Benefits to the Client: Clearly communicate the value AI brings to clients, such as improved efficiency, better lead targeting, and enhanced customer experiences.

Customizing AI Solutions

One size does not fit all when it comes to AI in sales. Sales Enablement Leaders must work closely with clients and prospects to customize AI solutions to meet their specific needs and objectives.

Needs Assessment: Start by conducting a thorough needs assessment. Understand the client’s pain points, goals, and existing processes. Identify areas where AI can make the most impact.

Tailored Solutions: Craft AI solutions that are tailored to the client’s unique requirements. This may involve integrating AI into their existing tech stack or developing custom AI algorithms.

Continuous Optimization: AI is not a one-time implementation; it requires continuous optimization. Ensure that your sales team is equipped to provide ongoing support and improvements.

Proving the ROI of Your AI Solutions With Confidence

Clients and prospects are likely to be interested in the return on investment (ROI) of adopting AI in their processes. Sales Enablement Leaders should be prepared to provide tangible evidence of how AI can generate positive results.

Case Studies: Share success stories and case studies of how AI has benefited other clients in similar industries or with comparable challenges.

Data-Driven Insights: Use data to demonstrate the impact of AI. Show how AI has increased lead conversion rates, shortened sales cycles, or improved customer satisfaction.

ROI Calculations: Work with clients to calculate the potential ROI of implementing AI. Consider factors like cost savings, revenue increase, and productivity gains.

AI Training and Adoption

Selling AI to clients and prospects is only the beginning. The successful adoption of AI within their organizations is equally crucial. Sales Enablement Leaders should emphasize the importance of training and change management.

Training Programs: Develop comprehensive training programs to ensure that client teams are proficient in using AI tools. This includes both technical training and understanding how AI fits into their processes.

Change Management: Understand that introducing AI can be disruptive. Provide guidance on managing the transition, addressing resistance, and fostering a culture of innovation.

The Criticality of Research-Based Tools for Selling AI

To effectively sell AI to clients and prospects, Sales Enablement Leaders should have access to research-based tools and insights. These tools can help in market analysis, competitor assessment, and staying updated on AI trends.

Market Research: Leverage market research tools to understand the demand for AI in specific industries. Identify niches where AI adoption is growing rapidly.

Competitor Analysis: Research what your competitors are offering in terms of AI solutions. Identify gaps in the market that your offerings can fill.

Trend Tracking: Stay informed about the latest trends and developments in AI. This knowledge can be used to position your AI solutions as cutting-edge and up to date.

Client-specific Insights: Utilize research tools to gather insights about specific clients and prospects. Understand their pain points, industry challenges, and preferences.

In the age of AI, Sales Enablement Leaders play a pivotal role in driving the successful adoption of AI solutions within their organizations and among clients and prospects. To excel in this role, it’s crucial to understand the AI landscape, build trust with clients, customize solutions, demonstrate ROI, and emphasize the importance of training and change management. Having access to research-based tools is instrumental in making informed decisions and staying ahead in the competitive AI market. As AI continues to reshape the sales landscape, Sales Enablement Leaders who master these themes will be well-positioned for success.

Request more information about IDC’s solutions for Sales Enablement leaders, new training solutions, market insights, interactive selling tools and business value calculators.

IDC recently published an assessment of vendors competing in the SD-WAN Infrastructure market and analysis of key trends driving this dynamic market. The 2023 IDC MarketScape on Worldwide SD-WAN Infrastructure evaluated 12 vendors in the SD-WAN market and recognized five leaders. 

“SD-WAN remains one of the most important markets in enterprise networking, driven by a variety of factors.”

Brandon Butler, Research Manager, Enterprise Networks, IDC

As organizations across the globe continue to embark on digital and network transformation initiatives, software-defined wide area network (SD-WAN) infrastructure remains a key technology that enterprises across the globe are investing in.

Organizations around the globe continue to invest in SD-WAN to optimize their edge network connectivity, enhance user and application experiences, enable increased operational efficiency, and save money.

Brandon Butler, Research Manager, Enterprise Networks, IDC

IDC forecast data shows that in 2022, the SD-WAN infrastructure market grew 25.0% and through 2027, the market will grow at a compound annual growth rate of 10.1% to reach $7.5 billion.

SD-WAN technology takes the principles of software-defined networking that were first deployed in datacenter networks and applies them to the wide area network. Fundamentally, SD-WAN technology abstracts the underlying WAN transports, such as broadband, MPLS, or cellular connectivity, from the software-based management of those networks.

Key Trends in SD-WAN

The SD-WAN market is in a state of transition. Since the market took hold nearly five years ago, vendors have been evolving their technology in a variety of important ways. Some important trends that are driving the SD-WAN market include:

SD-WAN + Security

There are multiple dimensions to the trend of more integrated management of SD-WAN and security. One aspect concerns the natively integrated security capabilities offered by SD-WAN vendors, such as intrusion detection and prevention (IDS/IPS), next-generation firewall (NGFW), and content/web/URL filtering.

A second aspect is toward secure access service edge (SASE) architectures, which combine SD-WAN with cloud-based network edge security as a service (NESaaS) tools, such as a secure web gateway (SWG), cloud access security broker (CASB), and zero trust network access (ZTNA). SD-WAN customers can work with their existing SD-WAN vendor to consume NESaaS and build a SASE architecture or use a multivendor approach.

The IDC MarketScape for Worldwide SD-WAN Infrastructure focuses on the networking strategy and capabilities of SD-WAN vendors, while also taking into account integrated and partner-led security approaches of SD-WAN vendors.

Another important trend is the software-defined branch (SD-Branch), which refers to integrated management of SD-WAN with LAN/WLAN networks. SD-Branch architectures create an opportunity for enterprises to have centralized visibility, analytics, and management of their network, across the LAN/WLAN and SD-WAN. Other benefits of SD-Branch include the ability for advanced ML/AI-enhanced management and leveraging a cloud-based platform. SD-Branch is ideal for customers that want to consolidate management across their campus and branch for ease of management.

2. SD-Branch: SD-WAN + LAN/WLAN

AI/ML-Enhanced Analytics and Automation

The visibility and automation platforms included in SD-WAN infrastructure products are maturing rapidly. Having insights into network performance and end user experience, and linking that data to advanced AI-enhanced automation systems becomes a powerful tool for enterprises that are managing globally-distributed SD-WAN deployments.

2023 IDC MarketScape for SD-WAN Infrastructure Evaluates 12 Vendors

The 2023 IDC MarketScape for Worldwide SD-WAN Infrastructure evaluates 12 vendors in the SD-WAN Infrastructure market across 20 scoring-criteria categories, including 10 each of strategy and capabilities. Vendors had to meet a minimum threshold of annual revenue and global availability of an SD-WAN Infrastructure product to be included in the research.

The research named five vendors as leaders, including Cisco, Fortinet, HPE Aruba Networking, Palo Alto Networks and VMware. Seven vendors were named Major Players or Contenders, including Aryaka, Barracuda Networks, H3C, Huawei, Juniper Networks, Nokia and Versa. Another three vendors did not meet the criteria to be included as full participants of the research but were named “Vendors to Watch” including Ericsson/Cradlepoint, Extreme Networks and NetSkope.

As organizations across the globe prioritize digital and network transformation efforts, SD-WAN infrastructure has solidified as a key strategic technology. The 2023 IDC MarketScape for Worldwide SD-WAN Infrastructure is meant to be a guide for helping enterprises evaluate vendors in this important, and fast-changing market.

In today’s rapidly evolving digital landscape, businesses across industries are recognizing the significance of application modernization as a strategic priority. The ability to adapt, innovate, and leverage emerging technologies has become crucial for driving digital transformation.

Professional services firms play a vital role in supporting organizations on this journey, offering their expertise to navigate the complex landscape of modern applications and modern application infrastructure options.

This blog explores the impact of application modernization on the ability of professional services firms to drive digital transformation now and in the next five years using data from a recent IDC Canada survey of medium and large businesses. Business leaders are urged to consider the growing importance of:

Security expertise.
Potential of packaged applications.
Rising need for updating and modernizing SaaS (Software-as-a-Service), PaaS (Platform-as-a-Service), and cloud-native applications.

Application Modernization as a Strategic Priority

According to a recent IDC Canada survey, over 50% of Canadian businesses currently rank application modernization as a top strategic priority for their organization. In the next 2 to 3 years, more than 75% of Canadian businesses surveyed expect application modernization to be a strategic priority for their organization.

The rapid advancement of technology, changing customer expectations, and the need for agility in a competitive market are driving organizations to overhaul their legacy systems, upgrade aging packaged applications, and update custom-built applications to embrace modern application solutions.

Professional services firms are well positioned to assist clients in this process by providing comprehensive strategies, implementation frameworks, and managed services methodologies that address the challenges associated with application modernization. The critical nature of application modernization services is so high that many ISVs are increasing their services capabilities through internal investments that enhance resources and service offerings. They are actively pursuing M&A opportunities, acquiring professional and managed services firms to extend the range and depth of their addressable market.

Security Expertise: A Vital Capability

As organizations embark on application modernization initiatives, survey results show that security expertise has emerged as the top-rated expertise requirement for professional services firms. With the increasing complexity of modern applications and the growing threat landscape, ensuring the integrity, confidentiality, and availability of data and systems has become paramount.

Professional services firms with robust security practices can guide businesses in adopting best practices, implementing robust security controls, and ensuring compliance with industry regulations. Their expertise enables organizations to navigate potential risks and safeguard their digital transformation journey. As with cost and value for money, security services are critical components to the buying decision of customers. This makes security services an essential feature for every sales pitch.

Packaged Applications: Seizing the Largest Opportunity

While application modernization encompasses a variety of software models, packaged applications present a significant opportunity for professional services firms in Canada. Using the same survey results, roughly ¼ of the average application portfolio is comprised of packaged applications such as enterprise resource planning (ERP) systems or customer relationship management (CRM) software. The survey also indicated that approximately 10% of the application portfolio is based on out-of-support packaged applications. A key application modernization strategy is the move away from traditional on-premises/client-server implementations using a variety of different options.

The market opportunity for professional services firms can range from helping clients in the selection process, customizing packaged applications with custom coding or add-on modules, and packaged application implementation to ensure the product works seamlessly across the entire enterprise and its application portfolio. This collaborative effort enables businesses to optimize processes, improve productivity, and accelerate their digital transformation initiatives.

The Future Landscape: SaaS, PaaS, and Cloud-Native Application Modernization

Looking ahead, the next five years will witness surging demand for updating and modernizing enterprise application portfolios using SaaS, PaaS, cloud-native, web-native, and mobile-native applications. The growing share of cloud, web, and native mobile applications comes at the expense of mainframe, custom, and packaged applications.

As businesses increasingly use cloud-based solutions and the enterprise software platform to drive business agility and scalability, the need to modernize and enhance these applications will become paramount. Professional services firms will play a pivotal role in assisting organizations with the migration, integration, and optimization of SaaS, PaaS, and cloud-native applications. By leveraging their expertise, these firms can ensure seamless transitions and enable businesses to harness the full potential of these modern technologies.

Conclusion

In order to capitalize on application modernization as a strategic imperative, professional services firms will still have to follow the traditional business axiom: meet the customers ‘where they are.’

In an area as complex as application modernization, there are a variety of solutions that buyers need to consider. The options for application modernization services start with five key considerations: development strategies, application tools, infrastructure considerations, application types, and service delivery. Additional options branch off from this starting point. The above figure illustrates some of the options for application modernization from both a buy-side and supply-side perspective.

In the era of digital transformation, application modernization has emerged as a critical enabler for organizations striving to remain competitive and meet evolving customer expectations, a view supported by IDC Canada’s research. Professional services firms, with their deep knowledge and experience, have a significant role to play in driving this transformation.

By recognizing the strategic importance of application modernization, investing in security expertise, and capitalizing on the opportunities presented by packaged applications and cloud-native solutions, professional services firms can empower businesses to navigate the complex landscape of modern applications successfully. As we move forward, these firms will continue to be instrumental in helping organizations unlock innovation, optimize processes, and achieve their digital transformation goals.

International Data Corporation (IDC) recently published its first IDC MarketScape for the worldwide quantum computing market, IDC MarketScape: Worldwide Quantum Computing Systems 2023 Vendor Assessment (IDC #US49607923, August 2023).

This study evaluated the seven circuit (gate-based) quantum computing hardware vendors that had developed circuit (gate-based) quantum computing systems. These vendors were offering access to these systems for a premium fee either through on-premises deployment, via the vendor’s quantum computing infrastructure-as-a-service (QCIaaS) offering, or a cloud service provider’s QCPaaS offering as of January 1, 2022. Eligibility was determined via information collected in a preliminary vendor survey and publicly available information. Quantum computing hardware vendors deemed eligible for inclusion in the study included: IBM, IonQ, IQM, PASQAL, Rigetti, Quantinuum, and Xanadu.

Interesting observations made over the course of the study include:

Quality trumps quantity: There has been a shift in the emphasis from the number of qubits making up a system to the quality of qubits that make up a system. Quantum hardware developers and vendors recognize that while being able to scale the number of qubits that make up a system is an accomplishment, it’s more important to deliver systems made up of qubits that perform with high rates of accuracy.
Hesitation in publishing detailed quantum computing developmental roadmaps: Many of the quantum hardware vendors are refraining from publishing detailed quantum computing developmental roadmaps. Learning from past experience, some quantum hardware vendors have found that publishing detailed roadmaps produces hype and a loss of confidence when deliverables and milestones are not met, even if the reason is related to unexpected technological challenges.
Customers prefer to work with quantum hardware vendors versus quantum cloud service providers: While quantum computing platform as-a-service offerings provide organizations an opportunity to experiment with different modalities of quantum, these providers often to know the systems as intimately as the quantum computing vendor.

Before expanding upon the methodology used for this study, it is important to note that quantum computing is still in the early stages of development. Because quantum computing technology differs considerably from classical computing infrastructure, both established technology vendors and quantum computing start-ups are designing and fabricating their quantum systems from the ground up. The complexity of the technology continues to challenge quantum hardware developers in their ability to deliver scaled systems that perform with the accuracy and speed that is needed to solve some of today’s most complex problems.

As a result, quantum hardware developers are taking different approaches as to how and when to market their technologies. Some quantum hardware developers are operating in stealth mode, making very little known about the developmental status of their quantum systems. Other quantum hardware vendors are re-evaluating and revising their quantum computing developmental strategy with the hopes of accelerating the production of their quantum systems. Finally, there is a group of quantum hardware vendors that began offering access to their systems after January 1, 2022. This study should be viewed as a snapshot of a dynamically changing quantum market. An announcement at any time by any vendor could drastically affect the way the market is currently viewed.

To gauge the current status of the quantum computing market, IDC’s MarketScape model was used to evaluate the quantum hardware vendors on their quantum computing strategies and capabilities. Evaluations and assessments of each vendor were made independent of each other. Based on these evaluations, a statistical methodology was used to determine the classification of each quantum hardware vendor as illustrated in the MarketScape graphic—leader, major players, contenders, or participants. The nine criteria were used to assess each quantum computing hardware vendor’s strategy. A different set of ten criteria were used to assess the quantum hardware vendor’s quantum computing capabilities.

While quantum computing is very much a nascent technology, strategic approaches are being implemented by quantum computing hardware developers with the expectation of being able to achieve a near-term quantum advantage using NISQ systems within the next five to seven years. During that time IDC expects that there will be many shifts with regards to the technology, as well as among the different players that make up the ecosystem itself.

The IDC report, IDC MarketScape: Worldwide Quantum Computing Systems 2023 Vendor Assessment (IDC #US49607923, August 2023), provides an assessment of worldwide quantum computing hardware vendors through the IDC MarketScape model.

Account-based marketing (“ABM”) is a strategic B2B marketing approach that targets a single company, division, or individual within a company. As such, it deploys far more targeted tactics than general marketing, designing campaigns around names and emails, individualized value propositions, and highly specific personas.

“Share of wallet” is one of the most important measures for developing an account and cultivating a lasting relationship. But it too often gets short-shifted as an element of ABM. Our experience has been that sales and marketing teams promoting IT often group existing accounts by vertical or size to allow for the creation of base content that can be refurbished or quickly personalized for specific customers. The focus tends to be on ranking customers by up- or cross-sell potential. Once complete, content creation kicks into gear.

But share of wallet can be taken further. IT suppliers can, of course, use share of wallet to better assess the potential for up-sells and cross-sells. But it can – and should – also be used to identify which clients deserve five-star service and which clients may need to be cut loose to free resources for others.

Show Me the Money

This is where market data comes into play.  

For instance, let’s say you work at an IT supplier with a suite of applications for data management. Let’s say you are assessing your customers in the United Kingdom. According to IDC data, in 2022, the retail space, Cazoo, Oasis Fashions, and Papa John’s International all spent around $1 million on data management software. In the transportation space, XPO Logistics and A.P. Moller-Maersk spent a bit less in the U.K.

Armed with that data, you can then find out how much they spent with you. It is a straightforward exercise to compare the total CRM spending of clients with the total you received. Simply create a table to compare the two and check your share of wallet.

Figure 1: Using Share of Wallet to Categorize Accounts

This allows you to do three critical things to improve your relationship and potential long-term revenue.

Recognize “Golden accounts”. These are accounts where you have a high share of wallet. It is important to keep the level in context. The threshold for what defines a golden account will differ by country, sector, and technology.  Once that threshold has been reached, it is unlikely to expand. Growth from the account will occur mainly through incremental service or product add-ons and expected price increases. In so doing, it is crucial to not “nickel and dime” these accounts. Rather, they should be targeted for extra attention, “reinforcement” or validation marketing, freemium advisory sessions, thank-you gifts (allowed by law and company policy), and your company swag. Basically, give them all the extra service and attention you can afford.


Identify growth accounts. The range on this can be quite broad and will differ based on the market, technology, and supplier. There is a good chance you have already named a fair number of these if your revenue and up-and-cross-sell activity has been growing either quarter by quarter or year by year. Market data helps validate those accounts to analyze why clients buy your tech or services, how tech is used, and the perceived value, which tells you whether to pursue account-specific outreach and content or leverage off-the-shelf assets.


Accounts to let go. It can be tough to admit a relationship isn’t working. It can be even tougher for a salesperson or their supervisor to let go of a stream of revenue. Share of wallet can help. As above, the share at which you choose to let an account go will vary. The key is to compare the share to what you are getting from other clients. If your share of wallet is averaging 30-40% and you have gone down around 5% and have barely budged in the past couple of years, it is probably time to evaluate whether the effort of maintaining them could be better spent on growth clients or acquiring new ones.

One final thought: If share of wallet is consistently low, there may be systemic issues at play that ramped-up ABM will not solve. The product itself could be cumbersome or the value proposition no longer unique. The sales and renewals processes could be overly complicated. Marketing and sales need to be more closely aligned. Or the competition has adopted a new approach that is proving successful.

In this respect, share of wallet can be multifunctional. All it takes is the right market data.

Since the launch of ChatGPT in November 2022, the media has been abuzz with all things Artificial Intelligence (AI), specifically with the concept of Generative AI. Even though these terms are decades old, at this point, it is safe to say that AI has come a long way. More recent advances in machine learning and deep learning have enabled computers to perform tasks that were once thought only to be wholly within the domain of human reasoning.  

According to IDC’s most recently published Worldwide Artificial Intelligence Spending Guide – which tracks the artificial intelligence (AI) spending for software, hardware, and services across industries and use cases – Canadian enterprises are expected to invest about C$ 5.2 billion on AI solutions in 2023. From 2022, this amount is expected to grow almost three-fold by 2027 at a compounded annual growth rate (CAGR) of 23.03%. 

Further, IDC expects the AI platforms, which includes technologies such as Conversational AI tools – the set of technologies behind automated messaging (text) and speech-enabled (audio) applications that offer human-like interactions between computers and humans – to cross more than C$2.2 billion, growing at a CAGR of 32.05% by 2027. 

Chatbot 2.0 Wars – Fueled by AI

Media buzz aside, one of the most exciting areas of AI research is Generative AI, which uses algorithms to generate new and unique content based on patterns and relationships learned from vast amounts of data. At its core, GenAI involves teaching a machine learning model to generate new content by training it on a dataset of existing content. 

ChatGPT stands for Chat Generative Pre-Trained Transformer, which is a chatbot developed by OpenAI. Both GPT 4 and GPT 3.5 belong to a family of large language models (LLMs) and are fine-tuned with supervised and reinforcement learning techniques, which are used by ChatGPT. Since GPT-4 is the newer of the two models, it comes with enhanced upgrades and improvements compared to its predecessor, GPT-3.5. 

The ‘large’ in LLM refers to the number of values or parameters used; to put things in perspective, OpenAI’s GPT-3.5 used approximately 175 billion parameters and was limited to information prior to June 2021 whereas GPT-4 is based on a lot more training data of over 1 trillion parameters and its data cut is up to September 2021. This gives the latter greater ability to handle much more nuanced instructions than its predecessor. Another stark difference between the aforementioned versions of ChatGPT is that GPT-4 is a multimodal model, which means it can process both text and image data, whereas GPT-3.5 is a text-to-text model.  

Microsoft, for its part, has also introduced ‘Bing Chat AI,’ uses GPT-4, an iteration of ChatGPT’s language models, combining web search, browsing and chat into one unified experience, producing more reliable and precise data compared to ChatGPT versions. 

Following suit, Google released its generative AI chatbot, BARD, earlier this year. BARD was initially based on company’s own LaMDA (Language Model for Dialogue Application System), but now uses the language model called PaLM or Pathways Language Model, which is more advanced and uses about 540 billion parameters. More recently, Google announced it is nearly ready to release its next-generation AI foundation model – Gemini – which is anticipated to outplay many of its competitors. 

Other big players such as Amazon and IBM are not far behind in this space and have made some notable announcements. Amazon’s proprietary LLM foundation models are known collectively as Amazon Titan and would be available through Amazon Bedrock service and other third-party companies. IBM, on the other hand, announced recently announced new GenAI foundation models and enhancements coming to WatsonX – the company’s AI and data platform. 

Canadian AI Market Opportunities

Given the recent innovation around the Generative AI space, IDC Canada expects that the next five years will be crucial in the adoption of AI-enabled software; businesses and enterprises of different sizes, as well as Federal and Provincial Governments, are expected to be obvious adopters. They are likely to adopt such technologies to stay AI relevant, but more importantly to create efficiencies, bolster automation, and remain agile.  

As per IDC’s Artificial Intelligence Spending Guide, Canada’s top three fastest-growing sectors in the Artificial Intelligence Platform space are Financial, Infrastructure and Manufacturing & Resources. 

Generative AI Limitations

While GenAI has shown incredible potential in a wide range of applications, several limitations must be considered when using this technology. Some of the most significant limitations of GenAI include:

Lack of control over output: Since the AI algorithms can produce original content, it isn’t easy to control the specific output.
Overfitting: too focused on specific data.
Limited dataset for learning: “You only know what you know.”
Bias loop: unfair or inaccurate output if the training data is biased.
Ethical concerns: deepfakes, copyrights, etc.

While these limitations are significant, they do not negate the potential of GenAI. In fact, these conversations about GenAI will help further increase AI awareness and an AI uptick in general.

Conclusion

As with any technology, challenges and ethical considerations must be addressed as the field of GenAI continues to evolve. And with GenAI’s benefits becoming ever more apparent, its impact on our lives and businesses will only continue to grow – making the conversations about its ”correct and fair” use of utmost importance. Overall, the versatility and potential of GenAI make it a very fascinating area of research, with many exciting developments and applications yet to be realized. Stay tuned. 

For more information on navigating the Canadian and global AI markets, refer to the following links or contact us today to learn more about IDC’s AI and GenAI data and analytics research.

Worldwide Semiannual Artificial Intelligence Infrastructure Tracker
Worldwide Artificial Intelligence Spending Guide
IDC’s Worldwide Artificial Intelligence Spending Guide Taxonomy, 2023
Generative AI Platforms and Applications: Market Trends and Forecast, 2Q23
OpenAI Announces Availability of GPT-4 for Improved Conversational Performance
Worldwide Artificial Intelligence Platforms Software Forecast, 2023–2027