In an era where technological advancements are reshaping our world at an unprecedented pace, Artificial Intelligence (AI) stands out as a beacon of innovation and progress. As we approach AI Appreciation Day this July, it’s crucial to reflect on the profound impact this technology has had across various sectors, from healthcare and finance to education and environmental conservation. This celebration serves as a reminder of the countless ways AI has enhanced our lives, streamlined our processes, and opened doors to possibilities once thought unattainable.
To commemorate this occasion, we’ve gathered insights from a diverse panel of industry experts, each offering unique perspectives on AI’s current state and future potential. These thought leaders share their experiences, highlighting both the challenges and triumphs in their respective fields. Their commentary provides a comprehensive look at how artificial intelligence is not just a tool, but a paradigm shift in how we approach problem-solving and innovation in the 21st century.
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Shailesh Manjrekar, Chief Marketing Officer, CloudFabrix
AI is going to change the way we work, live, and play! The biggest challenge is how do we democratize AI.
I have been associated with AI since my 1st job in 1992 with a premier research Institute in India – TIFR – Tata Institute of Fundamental Research and SAMEER – Society of Applied Microwave Electronics Engg. and Research, where we used AI to develop India’s 1st MST Radar – Meosphere, Stratosphere, Troposphere Radar. Since then I have been closely associated with the evolution of AI for Big Data Analytics, vertical use cases like Autonomous vehicles, Next Gen. Sequencing and Drug Discovery (Lifesciences), Precision Medicine and Healthcare, High Frequency Trading (FinTech), Industry 4.0 ( Smart Factory Automation) and of course in my current role for AIOps for Autonomus Enterprise. GPU Accelerated Computing then transformed AI with the availability of parallel processing and then found the killer App in Generative AI, which is transformational in democratizing AI. The rest is all history.
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Joel Stocker, Director of Product Marketing, ControlUp
As AI continues to advance, its integration into digital employee experience (DEX) strategies becomes indispensable. Leveraging AI to streamline root cause analysis, recognize anomalies, and shorten issue resolution times is revolutionizing how businesses operate. By embracing AI-driven DEX solutions, organizations can create a more dynamic and responsive work environment, significantly boosting productivity and setting themselves apart. Companies that harness the power of AI are not just improving their current operations but are also future-proofing their workforce.
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Subbiah Sundaram, SVP, Product at HYCU
On this AI Appreciation Day, we at HYCU celebrate AI’s role in solving problems once thought insurmountable. Protecting 35,000+ SaaS applications would have been unimaginable without AI’s power.
Our journey with Generative AI at HYCU is redefining data protection. We’re not just adapting to the AI revolution – we’re shaping it. By merging AI’s efficiency with our expertise in data, security, compliance, and resilience, we’re creating a future where data protection is powerful, responsive, and intuitive.
At HYCU, our work with AI sets a new industry standard. Our AI-driven development process, powered by Anthropic’s Claude model, transforms weeks of work into hours, accelerating development while ensuring stringent security requirements.
We’re also extending protection to AI infrastructure, safeguarding critical vector databases like PineCone and Redis, and massive data lakes. This holistic approach – protecting both traditional data and AI’s building blocks – prepares us for the next frontier of data protection.
Today, we not only appreciate AI but also harness its power to create a safer, more efficient digital world. This is the future of data protection, and at HYCU, we’re proud to pioneer AI in this way.
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Sundeep Goel, CEO DigitalEx
I’ve been in and around AI since 1992, my freshman year at Penn where I started my AI dual degree in Computer Science and Psychology. I’m incredibly excited about the recent pace of adoption across Enterprise IT with aggregate spend expected to exceed $1T/year by 2030.
At DigitalEx, we’re passionate about supporting this transformation but are concerned that many (most?) customers are not really aware of the true costs here. Even the cheapest tiers of dedicated LLM service are staggering from a cost perspective. We want to arm CFOs with the tools they need to better manage this spend – forecasting, budgeting, and chargeback/showback.
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Michael Gray, CTO of Thrive
Generative AI has captured everyone’s attention and is the newest buzz word across the globe. In fact, the global AI market is projected to grow from $86.9 billion in 2022 to $407 billion by 2027. While there’ s immense potential in the technology, generative AI should be approached with caution and awareness of the security risks associated with these tools. If, and when, businesses adopt generative AI they should take a pragmatic approach and consider taking the following steps:
- Clearly define how the tool will be used and the desired return on investment, like companies should for any technology purchase.
- Invest in training and education programs so employees have the skills needed to use gen AI effectively to reap the full benefits and avert the potential risks it poses.
- Develop processes and guidelines for ensuring the quality of AI output; for example, explicitly communicating what information should or should not be provided to the AI model to avoid data getting compromised.
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Madeleine Corneli, Lead Product Manager of AI/ML at Exasol
This AI Appreciation Day, most of us are focused on the impact of generative AI (GenAI). However, this is also a great time to acknowledge the ongoing impact of classic AI. Classic AI excels at pattern recognition and often better meets stricter business requirements. Forecasting, categorization, and scoring are consistent applications of classic AI that will remain relevant to businesses and don’t necessitate LLMs. Furthermore, explainability and repeatability are regulatory requirements that cannot be met by GenAI and certain businesses or use cases can not tolerate the hallucinations that can come with GenAI. We should think of classic AI and GenAI as complimentary – each brings unique strengths and value.
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Ugur Tigli, CTO at MinIO
Successful AI demands scale and speed – as companies grow, they need a fast and easy way to manage and store all of their data. The limited availability of GPUs is pressuring many companies to move their AI operations to the public cloud, but this could be a mistake depending on the workload, especially AI workloads.
As AI continues to progress, leaders must consider how their data storage will impact their long term AI strategy. With data storage requirements reaching exascale, there is no public cloud model that supports keeping data in the cloud with its data access and egress charges. Everything you do in the public cloud, you can do on the private cloud – at a savings of 60% plus. Additionally, when flexibility and control are a high priority, locking your enterprise into a public cloud ecosystem that will be difficult to extract from once the bills start arriving is not the ideal choice.
The private cloud, whether colocation services or datacenter, is the path forward for AI workloads that the CTO, CIO and CFO can all agree on.
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Graham Glass, CEO and CTO of CYPHER Learning
AI is a transformative technology that runs on trust as much as on lines of code, so organizations must introduce AI technology in tandem with human oversight. It’s important that we not mistake today’s early-stage iterations of AI as the finished product – they represent baby steps, or “raw” expressions of what’s possible. We are heading toward a world of assistive, controlled AI implementations where today’s errors and missteps diminish, but it will win hearts and minds only when people have confidence in it.
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Dr. Lisa Graham, CEO, Seeq
Ensuring ethical AI usage and maintaining data privacy and security involves several best practices:
- Invest in the Right Skills: Train your workforce in data science and AI to develop in-house expertise.
- Define Standards: Establish robust data governance practices to ensure data quality, privacy, and compliance with industry regulations.
- Start Small: Begin with pilot projects to test AI applications before scaling up.
- Encourage Continuous Learning: Foster a culture of continuous learning and adaptation as the technology evolves.
- Human Oversight: Ensure AI applications have human oversight to maintain transparency and accountability.
- Data Privacy: Implement strong data encryption, access controls, and anonymization techniques to protect sensitive information.
- Ethical Guidelines: Develop and adhere to ethical guidelines that address fairness, accountability, and transparency in AI applications.
One major trend is the integration of AI with advanced analytics platforms, which will further enhance decision-making and predictive capabilities across various industries. Another significant innovation is the development of generative AI, which increases the ability of analytical techniques to detect anomalies, inform predictive maintenance, and forecast production data. Additionally, AI-powered conversational and interactive user interfaces will simplify onboarding and training processes. As AI technology continues to evolve, we can expect more seamless integration into business operations, leading to enhanced productivity and efficiency. The focus on ethical AI and data privacy will also shape future developments, ensuring that AI applications are both powerful and responsible.
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Dan Faulkner, Chief Product Officer at SmartBear
In the past few years, we’ve seen many organizations implement AI washing, in which they rush to get AI into their products even when it doesn’t make the most sense. At SmartBear, we believe our job is to figure out what the customer needs, and from that determine what we can do to help them achieve new heights by producing newer and/or better work. So, as we look to integrate AI into our products, we view GenAI as an enabler. For developers, this can mean using it to create more resilient software tests that have self-healing and are simpler to develop and maintain; to standardize efficiency and quality improvement in application testing; and to look for opportunities to integrate AI across the API lifecycle.
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Jake Varghese, Executive Vice President and General Manager of Business Management, ConnectWise
AI has already started to solve complex problems for Managed Service Providers (MSPs). The power of AI combined with Robotic Process Automation (RPA), all powered by a purpose-built platform for MSPs, is where the magic truly happens, generating automated workflows on organizations’ behalf and with their approval to drive bottom-line impact.
When organizations and MSPs are equipped with AI, these businesses can work smarter, become highly innovative, and be more responsive to their customers. In addition to benefiting operations, AI is also helping to improve customer experiences, productivity, and overcome knowledge fragmentation.
My advice is don’t wait until it’s too late and risk falling behind. This AI Appreciation Day, organizations must adopt AI-driven solutions that optimize and simplify business operations worldwide.
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Carl Froggett, CIO, Deep Instinct
AI holds immense promise, but not all AI is equal. All AI, apart from deep learning, is currently being promoted to cover up failures of machine learning, specifically to reduce process overhead; plus, organizations expect customers to pay a premium for these services. AI holds so much more promise. When leveraged correctly, AI can streamline internal processes, alleviate repetitive and time-consuming tasks, and ultimately, transform industries.
However, the only way to stay ahead of increasingly sophisticated attackers is to remove traditional AI tools and innovate with better AI, specifically deep learning. This advanced form of AI prevents threats from ever landing inside an environment with a prevention-first approach. SecOps teams are finally realizing deep learning’s true potential to leap ahead of legacy, reactive cybersecurity approaches and fight back in the continuous cat-and-mouse game against cybercriminals.
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Matt Psencik, Director, Endpoint Security Specialist, Tanium
Since becoming mainstream nearly two years ago, generative AI has served as a helpful, supplemental resource for cybersecurity professionals – reducing research time, sifting through mundane, time-consuming tasks, and making complex tasks easier to understand.
A good example of this is the ability to take a snippet of code – whether hex, assembly, or a high-level language like python or C++ – and have generative AI explain each section of code. While there may be some errors, the technology can serve as an on-demand digital expert, educating those newer to the industry, expanding skill sets, and increasing efficiency for those bogged down with alerts.
However, it’s important to note that AI is only as good as the data it’s fed, so the best use of AI is when it’s powered by real-time data. This reduces errors and gets cybersecurity teams the most up-to-date information they need to properly defend their organization.
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Patrick Harding, Chief Product Architect, Ping Identity
AI has opened doors for nearly every industry, including cybersecurity, as it has allowed organizations to become more proactive against threats, create more frictionless user experiences, and stop attackers in their tracks faster than ever before. Yet, just as AI has been a force for good, it’s also been a catalyst for threat actors to increase their sophistication, putting identity under attack. This kind of activity is on the rise, with 41% of IT leaders expecting cybercriminals’ use of AI to significantly increase identity threats over the next year. That said, today should serve as a reminder that while AI has created challenges for security, there is also a great opportunity to embrace the emerging technology. More specifically, organizations can (and should) use AI to combat AI-related threats and stay one step ahead of cybercriminals, to protect their customers and employees alike.
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Jim Palmer, Chief AI Officer, Dialpad
The growth of AI over the past five years alone has been tremendous, and this year was the year AI became real and tangible for businesses and consumers. Beginning to demonstrate its true ROI, AI has begun to transform the way we work, communicate, collaborate and innovate. AI tools have already started to revolutionize industries, like sales and customer service, to save users time, unlock invaluable insights and deliver experiences that we could only imagine years ago.
When used for good with human oversight, AI adoption has the power to boost businesses to new heights. In fact, 77% of leaders believe AI will provide them with a competitive advantage, allowing them to increase productivity and customer satisfaction to significantly grow their business. And while there is so much more to refine and improve about the emerging technology, I look forward to the advancements the coming year will bring and am hopeful for continued investment in responsible AI.
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Kaarel Kotkas, Founder & CEO at Veriff
Over the past year, almost 78% of US decision-makers have seen an increase in the use of AI for fraudulent attacks. AI technology enables cybercriminals to up their game, from stealing our data to copying our likeness. However, AI technology is both the sword and the shield. AI can also help an organization combat fraud, and 79% of CEOs are actually using it to do so.
This AI Appreciation Day, leaders should focus on the benefits of the technology while preparing for impending fraud attacks. An effective fraud defense must be dynamic and multi-faceted. Incorporating AI as a layer of defense against fraud will keep bad actors at bay and limit any potential friction in the customer journey. It’s important to remember that there is no one-size-fits-all solution to combating fraud, so leaders must implement multiple types of solutions that can complement and augment existing security measures. Technology has yet to evolve to a point where it requires no human intervention, and AI systems will likely always need some level of human touch for quality control. Human feedback in AI decision-making is necessary in its formative stage to ensure the models improve. If an AI system isn’t 100% positive that a potential user’s ID is fraudulent, a human needs to determine the next steps.
Fraudsters constantly evolve their technology, so fraud techniques will continue to become more sophisticated. When it comes to improving cybersecurity while countering these new AI-powered attacks, companies cannot be afraid to invest in tech. Using AI-powered technology to combat fraud and build out your deepfake detection capabilities opens up opportunities to stay ahead of the curve. If leaders follow this process, their defenses will continue to get stronger.
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Dr. Torsten Staab, Principal Technical Fellow at Nightwing
While the capabilities of AI are tremendous and the potential under its influence seems vast, AI Appreciation Day is the perfect time to reflect on how this groundbreaking technology has shaped our day-to-day lives and the ways in which we operate. There is no question that AI will have a profound impact on the future of technology, but with all of its buzz and excitement also comes recognition of its limitations.
For example, addressing AI bias is crucial for building trust in AI systems and ensuring they work fairly for everyone. It involves a combination of technical solutions, diverse teams, and ongoing monitoring to ensure biases are identified and mitigated. Unfortunately, there is no easy-button solution to solving AI bias risks. Addressing bias in AI-powered systems or services requires a multifaceted approach, encompassing technical, organizational, and ethical strategies.
Of course, the goal is not to instill fear or distrust of AI, but rather, to foster an environment of informed and responsible use. AI is a tool, and like any tool, it has its intended uses and its limitations. And how effectively it is used depends on the skill and knowledge of the person using it. Ultimately, we can harness the power of AI while still safeguarding against its pitfalls if we remain dedicated to the continuous improvement of this technology, ensuring these systems are not only intelligent but also impartial.
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Kevin Bocek, Chief Innovation Officer at Venafi
Many organizations appreciate AI because of its positive benefits on day-to-day tasks. It helps save time, automate tedious tasks, increase creativity, and more. But with that comes security concerns, increased risks, and malicious activity including AI-generated code, reverse engineering existing programs, and injecting incorrect or harmful content into otherwise legitimate models. To keep organizations secure, I recommend ensuring an AI “kill switch” is in place to quickly turn off any AI models to prevent destruction or security implications. We need to uniquely identify each model, control its use, and what it is allowed to do based on its unique identity. AI is just another machine, and understanding this will eliminate breaches we’ve seen time and time again where identity security – of APIs, of code, of cloud, of malware – has been an afterthought.
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Assaf Baciu, Co-Founder and President, Persado
While businesses have raced to adopt AI to improve operations and performance, many are still struggling to find a way to prove the value. In marketing, however, AI has been making an impact for a while–and we already have the data to back it up. At Persado, we have a decade of proof of value for AI. We’ve had a front row seat to GenAI actively helping brands personalize on-brand marketing content to increase engagement and conversions across channels.
By applying learnings to make precise changes in words and phrases, brands can drive completed transactions, applications or enrollments, and unlock a new lever for growth. This use of AI not only drives relevant, engaging customer experiences; it’s easy to measure, empowering business leaders to make better decisions and drive sales. In fact, Persado has worked with the world’s top banks and card issuers for years, driving $2.5 billion in incremental revenue using purpose-built AI proven to increase productivity and performance.
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Chris Savage, CEO & Co-Founder, Wistia
When it comes to AI, AI-generated videos are top of mind for me right now. They hold a lot of promise for video creators, and the demand is there: more than half (66%) of organizations are eager to use AI for their video projects. But with AI-generated videos comes the risk of losing the human element; which is something we need to hold on to in order to keep the trust and integrity of the content.
The best way to leverage AI is to improve existing offerings, integrating it into every day user interfaces. Listen to customer feedback and identify pain points that you can supplement with AI. Pinpoint where you can streamline workflows, increase efficiency, and create more personalized and intuitive user experiences. This will not only improve the customer experience and build trust, but also evolve the product – instead of solely jumping into the hype that comes with AI-generated videos.
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Prukalpa Sankar, co-founder, Atlan
The CDOs and CIOs I talk to are mostly getting asked the same question by their CEO, “What’s our AI roadmap?”. It’s a complex question to answer because it involves so much more than which AI model to use and what systems to connect it to. The enterprise companies we work with are at varying stages of maturity, but for the ones who have defined and prioritized use cases for AI, the big challenges we’re helping them with are first, getting to AI-ready data – data that’s enriched with context, trust signals, and security that an AI model can consume – and second, governing AI models to ensure they use the right data and provide the right response. In addition to the familiar “Garbage In, Garbage Out” risk with using data, AI has the added risk of “Garbage In, Gospel Out”, making AI-ready data and AI governance essential to successfully using AI.
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Nabil Hannan, Field CISO, NetSPI
AI is a polarizing topic in the cybersecurity industry, as it has simultaneously driven a surge in cyberattacks and served as a transformative tool for defending against them. In the past year, we’ve seen an immense increase in companies adopting AI technologies. In the proactive security industry in particular, AI capabilities have enhanced the ability to monitor threats, analyze user behaviors, and identify potential risks/exposures in real-time. Ultimately, these advancements have created a better user experience and enabled organizations to accelerate innovation faster than ever before. Looking ahead, I’m excited to see how AI will continue to grow the cybersecurity landscape and better equip security teams with the resources they need to discover, prioritize, and remediate threats of the highest importance.
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Jeff Gallino, CEO and Founder, CallMiner
Automation technology has long been used in contact center and customer service applications, but the promise of large language models and generative AI (ChatGPT, anyone?) have renewed this focus. While AI is not a cure-all, when used thoughtfully and responsibly, it can enhance both the contact center agent and customer experience (CX).
With the goal of augmenting human capabilities, rather than replacing them, AI is already helping organizations sift through large volumes of structured and unstructured customer data to uncover trends and opportunities – those needle-in-a-haystack moments – and deliver better CX. It is also guiding and delivering knowledge to agents in real time, uncovering important signals such as vulnerability or dissatisfaction, and helping them connect with customers on a deeper level.
There is a lot to appreciate when it comes to AI, and in many respects, we’re just getting started. Yet, we can all recognize the value AI will undoubtedly bring to a wide range of industries and use cases, while also staying mindful that the most powerful applications will be those that are carefully considered, tested and implemented.
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Alex Triplett, CFO/COO, Appfire
AI is making an undeniable impact across industries and organizations, and will dramatically transform how business is conducted for years to come. Just like any phenomenon that has the potential to transform our work, it is critical to incorporate it into a company’s strategy across the organization at every level, and not keep it siloed to one dedicated individual or team. Whether your company has a strong tech focus or not, it would be a misstep to hire one sole individual who is responsible for overseeing AI’s adoption and implementation within your organization. AI, like the internet before it, will change everyone and should be championed by everyone!
On AI Appreciation Day, it’s important to recognize that AI should be an integral part of your organization’s holistic thinking, and every C-suite member should be an expert in their own domain. This is a better way to ensure that everyone within your organization can keep pace with the innovation and changes associated with AI, and most importantly embrace and understand such changes.
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Matt Forrest, Field CTO, CARTO
When GPT-3 was introduced to the world, the overwhelming public response was a clear indication of the transformative potential of models like ChatGPT. However, with individual users and many businesses immediately reacting to the generative AI boom, we’ve learned a critical lesson about the importance of context and integrating first-party data when deploying AI. Unlike a year ago, we now have a better understanding of the necessity to integrate AI with proper context, supported by advanced vector databases, and underscored by robust security, privacy, and ethical frameworks to ensure the effectiveness of any specific use case.
As we celebrate the strides made in AI, it’s evident that our journey is just beginning. Looking ahead, I’m eager to see the development of more specialized tools leveraging AI models and, more broadly, how AI technology will mature alongside those using it. Specifically, a use case I’m excited about is the ability to use AI to pull insights from digital maps and geospatial insights. For example, using AI in Spatial Data Science in the telecommunications industry can help users determine the number of individuals in a certain location who are experiencing below-standard 5G coverage or towers in the path of a wildfire. I expect organizations across every industry to continue exploring AI’s capabilities to identify ways to improve their operational productivity, product quality, and beyond.
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Ryan Tierney, SVP of Product Management at TrueCommerce
The global supply chain is being challenged every day with volatility, rising costs, and sustainability. By harnessing the power of AI, businesses can optimize their supply chains by using AI-powered algorithms that can analyze vast amounts of data, to make informed decisions regarding production volumes, inventory levels, and distribution strategies. AI also plays a crucial role in automating repetitive tasks by utilizing machine learning and robotic process automation to streamline warehouse operations, order processing, and transportation logistics. With AI, companies can also enhance their QA processes with technologies that will automatically detect defects or anomalies in products during the manufacturing process.
For organizations, embracing AI-driven solutions is not only a strategic move, but a necessity for operational efficiency, reducing costs, and improving customer satisfaction in today’s digital and interconnected world of global commerce.
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Bill Salak, CTO & COO of Brainly
AI already provides exciting use cases that can impact our everyday lives – but its maturity is still taking hold. Artificial intelligence is unfolding rapidly, and we can expect more revolutionary applications as we enter a phase of grounded and responsible AI innovation. With technology this sophisticated, it takes time to discover the most effective implementations across various sectors and aspects of society. What we’ve seen is just the beginning – ongoing innovation and refinement by developers, coupled with an improved understanding of AI’s applications among users, will bring AI’s full potential to reality. It’s an incredible time to be in the technology sector, and I’m excited to be part of it.
Working in the edtech space, we use AI to help students reach learning outcomes via personalized education plans. AI took my 5-year product roadmap and condensed it down to one. We’re thrilled about what we’ve achieved and what we’ll be able to offer K12 students in the future.
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Cheryl Johnson, Chief Product & Technology Officer of Betterworks
Generative AI promises to fundamentally impact the interaction between human and machine forever. The buzz surrounding AI and how it will affect the way we work cannot be ignored. There is a vast opportunity in front of all of us — and especially HR leaders.
I’m optimistic that AI will help HR teams transform workforce performance by doing things like detecting and eliminating unconscious bias from the performance evaluation process, boosting goal quality, encouraging goal achievement, simplifying the arduous process of conducting performance reviews, prompting timely recognition, providing tailored coaching suggestions, and much more. It will help employees work faster, smarter, and more productively. It will help managers in becoming better managers and coaches.
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Sara Gutierrez, Chief Science Officer of SHL
As organizations rapidly adopt AI technologies, we are likely to see a significant skills gap that could make it challenging for organizations to thrive. This gap encompasses not only the technical AI skills necessary for developing and managing AI systems but also the universal human skills essential for effective human-AI collaboration.
Talent Intelligence platforms can play a crucial role in addressing the skills gap. These platforms provide a comprehensive understanding of candidate skills, experiences, and potential by analyzing diverse data sources such as psychometric assessments, job performance metrics, and self-reported skill proficiencies. By leveraging AI and Talent Intelligence data, organizations can drive a broader and deeper understanding of internal and external candidates’ skills and abilities, moving beyond traditional résumé-based evaluations. AI algorithms can identify patterns and correlations in the data that predict success in specific roles, allowing for more precise matching of individuals to positions where they are most likely to thrive.
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Kirimgeray Kirimli, President of Flatiron Software
AI is revolutionizing work life by transforming how we approach our daily tasks and make decisions. With Snapshot Reviews, we leverage AI to create a fairer system for evaluating engineer performance and productivity. Our AI powered application has the ability to process vast and diverse data sources and enables managers to deliver accurate, unbiased feedback, creating equal opportunities for all. This not only benefits organizations by aligning team efforts with strategic goals but also empowers individuals by recognizing their true contributions and fostering continuous growth. Using AI in the workplace is essential to promote a culture of transparency, equity, and high performance.
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Soufiane Amar, CEO and Founder of Shreds.AI
We firmly believe that AI won’t steal jobs; instead, it will create new ones. Yes, there will be significant changes in many fields, but these changes will bring forth exciting new opportunities.
In our industry, we pride ourselves on being pioneers. Shreds.AI has developed an AI capable of generating complex software from simple descriptions. Naturally, this has raised questions and concerns among developers about whether this AI will replace their jobs. The simple answer is: Absolutely not.
By making software development faster and more affordable, companies will be able to use more software in various scenarios, creating more value and automating more processes. This automation leads to increased efficiency and productivity, opening up even more job opportunities.
Every piece of software generated by our AI must be validated by a developer. Therefore, while the role of developers may shift towards expertise and validation, the demand for their skills will only grow. The future holds more jobs than ever, driven by the innovations and efficiencies that AI brings.
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Matt Hollingsworth, Co-Founder of Carta Healthcare
Although the adoption of AI in healthcare is nothing new, there will continue to be a growing need for AI technology in 2024 and beyond. With an overall lack of manpower in healthcare, as seen in nursing and staff shortage trends, AI looks like the best solution for retaining existing manpower at competitive compensation rates while increasing efficiency in workflow and improving clinician job satisfaction. According to the National Library of Medicine, the key to successful AI implementation is to do it in a clinically relevant way that clinical caregivers can get behind. It’s not only about the technology, it’s about how technology and caregivers work together in a trusted way to believe in, train, and commit their AI solutions to provide long-term value.
AI applied in healthcare data analysis and abstraction can assist doctors in determining treatment plans for patients. When analyzing a data set, AI can help reveal potential problems based on data; what previous medications a patient has taken, their medical conditions, what procedures they have had, and beyond. In its intended capacity, this technology can assist providers in making better informed decisions about patient care.
In terms of real-world medical applications, ChatGPT could be used to help doctors write up summaries after they visit with patients. This would not only save clinicians time, but it could also improve their communication cadence, as not everyone is a great writer. ChatGPT can improve the speed in which patients receive answers from doctors, as long as the doctor is still reviewing and approving any information before it is being shared with a patient. Further, If we can find ways to use ChatGPT to help nurses with administrative tasks, we can lessen their workload, decrease burnout, and hopefully improve the nursing shortage.
Unlike in other fields where AI can train itself, healthcare AI requires a guided process with humans actively involved in training the technology. There is also no quick fix to the problem of healthcare data intricacy. However, one proven method of gaining health leaders’ trust in AI is to have certified healthcare data experts take on the dual process of performing their tasks while AI training. As the trainers familiarize themselves with the technology, the latter also grows its capability of performing tasks accurately. Although the full training process can take up to several years to complete, this human-centric approach both improves AI in healthcare’s accuracy and impact, as well as provides a solution to other prevalent issues such as cost and the nursing shortage.
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Dom Esposito, CEO & Co-Founder JJJ International Inc.
There is a need to emphasize the profound impact AI is having on the frontline workforce, particularly in hospitality, retail, healthcare, and manufacturing. AI is fundamentally transforming labor distribution trends, shifting from permanent full-time positions to flexible roles. By computing large data-sets to intelligently match best-fit workers with the right opportunities, it not only boosts productivity and efficiency but also makes work more adaptable and rewarding. I’m optimistic about AI’s potential to optimize resourcing strategies, create more dynamic and flexible workforces, and ultimately create more opportunities for the next-gen workforce.
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Shawn Rosemarin, Vice President R&D – Customer Engineering, Pure Storage
In the fast-evolving landscape of AI, it’s critical that organizations balance the importance of robust infrastructure with operational efficiency and sustainability in order to support their AI ambitions. While the public cloud can be a great place to test and prove out the viability of these new solutions, many enterprises will deploy their training data and models in-house. With this in mind, hybrid cloud extensibility is becoming a critical enabler of success. By thoughtfully planning infrastructure investments with a keen eye on operational overhead and long-term sustainability organizations can mitigate rising cloud costs and responsibly unlock the full potential of AI.
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Shashi Prakash, co-Founder and CTO, Bolster
There is a mounting sophistication to AI-fueled deep fakes and cyberattacks, particularly those targeting high-profile individuals like politicians and company executives. Generative AI is assisting adversaries in quickly setting up fake profiles across multiple channels including LinkedIn, Telegram, WhatsApp and other social platforms, to establish legitimacy before targeting your customers, employees or partners with a phishing or impersonation scam, a typosquat attack, spoofed domain or fake mobile app. We encourage everyone to become even more alert and critical than before when replying to unfamiliar email or clicking links sent via text. While we expect these fraudulent activities to increase in frequency and severity, we know through our development work and use of AI that the news around it is not all bad.
On AI Appreciation Day, we know that countering AI attacks at scale, especially for executive protection, is infinitely more effective through the use of AI for detection and remediation. We also want to recognize and acknowledge the many positive advancements in our lives because of AI and machine learning. These range from AI as a driver of business innovation to automate business operations, reduce costs and improve consistency and speed of daily tasks. It is also an especially effective tool as a powerful defense mechanism against many threats that we know and those we have not yet seen. In this spirit, we share the belief that AI is creativity and human innovation at its best. We believe strongly in responsible use with the highest regard for AI’s power.
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Ojas Rege, SVP & General Manager, Privacy & Data Governance, OneTrust
As AI becomes more deeply embedded into business models and people’s daily lives, the ethical and legal obligations of each organization to use AI responsibly increase. AI systems center on data, and many organizations feel the pressure to collect more data, create richer proprietary datasets, and use AI as a competitive advantage. However, models do not easily “unlearn” if trained on poor data, and if models are trained on inappropriate or non-compliant data, they might have to be decommissioned or retrained from scratch at great cost to the business. Violations are also subject to a new FTC penalty called “algorithmic disgorgement,” which requires destroying an AI model or set of algorithms if an organization is found to have trained that model on illegally obtained data. These penalties may also restrict the organization’s use of that technology moving forward.
The ubiquity of AI across software systems also requires an organization to look beyond its own four walls to its hundreds or thousands of software vendors and partners that are integrating machine learning models into their own offerings. This ecosystem creates an entirely new vector of risks that must be assessed by every organization across its supply chain.
The answer to these risks and penalties is not to reduce investment in AI, but rather embed AI governance early in the development and procurement process so that appropriate risk assessment and mitigation measures become early enablers, not late-stage gates, for the business. For example, an organization must fully understand the training data going into its own models and those of its partners before it is used. AI governance that starts at the point of project design and data collection is one of the most effective ways to minimize future privacy, security, and ethical issues with AI.
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Aviral Verma, Lead Threat Intelligence Analyst, Securin
We are on course towards Artificial General Intelligence, or AGI, where AI goes beyond imitation and can exhibit human-like cognitive abilities and reasoning. AI that can grasp the nuances of language, context and even emotions. I understand the side of caution, the fear of AI replacing humans. But I envision this evolution to enhance human-AI symbiotic relationships, where its true potential lies in complementing our strengths and weaknesses. Humanity is a race of creators, inventors, thinkers, and tinkerers; AGI can help us be even better at all those things and act as a powerful amplifier for human ingenuity.
To promote safety for all users and responsible AI deployment, developers must uphold Choice, Fairness, and Transparency as three critical design pillars:
- Choice: It’s essential that individuals have meaningful choices regarding how AI systems interact with them and affect their lives. This includes the right to opt-in or opt-out of AI-driven services, control over data collection and usage and clear explanations of how AI decisions impact them. Developers should prioritize designing AI systems that respect and empower user autonomy.
- Fairness: AI systems must be developed and deployed in ways that ensure fairness and mitigate biases. This involves addressing biases in training data, algorithms and decision-making processes to prevent discrimination based on race, gender, age or other sensitive attributes. Fairness also encompasses designing AI systems that promote equal opportunities and outcomes for all individuals, regardless of background or circumstances.
- Transparency: Transparency is crucial for building trust in AI systems. Developers should strive to make AI systems understandable and explainable to users, stakeholders and regulators. This includes providing clear explanations of how AI decisions are made, disclosing limitations and potential biases, and ensuring transparency in data collection, usage and sharing practices. Transparent AI systems enable scrutiny, accountability and informed decision-making by all parties involved.
The tech industry is on the edge of something truly exciting, and I am optimistic about the advancements individuals and organizations can achieve with AI. To build confidence in AI, we should focus more on Explainable AI (X-AI). By clarifying AI’s decision-making processes, X-AI can alleviate the natural skepticism people have about the “black box” nature of AI. This transparency not only builds trust but also lays a solid foundation for future advancements. With X-AI, we can move beyond the limitations of a “black box” approach and foster informed, collaborative progress for all parties involved.
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Anthony Cammarano, CTO & VP of Engineering, Protegrity
On this AI Appreciation Day, we reflect on AI’s remarkable journey to an everyday consumer reality. As stewards of data security, we recognize AI’s transformative impact on our lives. We celebrate AI’s advancements and democratization, bringing powerful tools into the hands of many. Yet, as we embrace these changes, we remain vigilant about the security of the data that powers AI.
Vigilance takes understanding the nuances of data protection in an AI-driven world. It takes a commitment to securing data as it traverses the complex pipelines of AI models, ensuring that users can trust the integrity and confidentiality of their most sensitive information. Today, we appreciate AI for its potential and challenges, and we renew our commitment to innovating data security strategies that keep pace with AI’s rapid evolution.
As we look to the future, we see AI not as a distant concept but as a present reality that requires immediate attention and respect. We understand that with this great power comes great responsibility, and we are poised to meet the challenges head-on, ensuring that our data-and, by extension, our AI-is as secure as it is powerful. Let’s continue to appreciate and advance AI, but let’s do so with the foresight and security to make its benefits lasting and its risks manageable.
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Kathryn Grayson Nanz, Senior Developer Advocate, Progress
This AI Appreciation Day, I would encourage developers to think about trust and purposefulness. Because when we use AI technology without intention, we can actually do more harm than good. It’s incredibly exciting to see Gen AI develop so quickly and make incredible leaps forward. But it’s also a responsibility to build safely with a fast-moving technology.
It’s easier than ever before to take advantage of AI to enhance our websites and applications, but part of doing so responsibly is being aware of the inherent risk – and doing whatever we can to mitigate it. Keep an eye on legal updates, and be ready to potentially make changes in order to comply with new regulations. Build trust with your users by sharing information freely and removing the “black box” feeling as much as possible. Make sure you’re listening to what users want and implementing AI features that enhance – rather than diminish – their experience. And establish checkpoints and reviews to ensure the human touch hasn’t been removed from the equation, entirely.
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Arti Raman (She/Her), CEO and founder, Portal26
Generative artificial intelligence (GenAI) offers employees and the C-suite a new arsenal of tools for productivity compared to the unreliable AI we’ve known for the past couple of decades, but as we celebrate these advancements this AI Appreciation Day, it’s less clear how organizations plan to make their AI strategies stick. They are still throwing darts into the dark, hoping to land on the perfect implementation strategy.
For those looking to make AI work for them and mitigate the risks:
1. The technology to address burning security questions regarding GenAI has only been around for approximately six months. Many companies have fallen victim to the negative consequences of GenAI and its misuse. Now is the time to ask, ‘How can I have visibility into these large language models (LLMs?).’
2. The long-term ability to audit and have forensics capabilities across internal networks will be crucial for organizations wanting to ensure their AI strategies work for them, not against them.
3. These core capabilities will ultimately drive employee education and knowing how AI tools are best utilized internally. You can’t manage what you can’t see or teach what you don’t know. Having the ability to see, collect and analyze how employees use AI, where they’re most using it and what they’re using is invaluable for long-term strategy.
AI has marked a turning point globally, and we’re only at the beginning. As this technology evolves, so must our approach to ensuring its ethical and responsible usage.
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Roger Brulotte, CEO, Leaseweb Canada
In an age where “data readiness” is crucial for organizations; the rapid adoption of AI and ML highlights the need of cloud computing services. Canada stands as a pioneer in this technological wave, with its industries using AI to drive economic growth. Montreal is quickly establishing itself as an AI hub with organizations like Scale AI and Mila – Quebec Artificial Intelligence Institute.
Companies working with AI models need to manage extensive data sets, requiring robust and flexible solutions to manage complex tasks, training large datasets and neural network navigation. While the fundamental architecture of AI may remain constant, scaling the components up and down is essential depending on the model’s state. As the data-driven landscape keeps evolving, organizations must select data and hosting providers who can keep up with the times and adjust as needed, especially as Canada implements its spending plan to bolster AI on a national level.
On AI Appreciation Day, we recognize that superior AI outcomes are powered by data, which is only as effective as the solutions that enable its use and safeguarding.
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Steve Wilson, CPO, Exabeam
My recognition of AI Appreciation Day is part celebration, part warning for fellow AI enthusiasts in the security sector. We’ve seen AI capabilities progress dramatically, from simple bots playing chess, to self-driving cars and AI-powered drones with a spectacular potential to truly change how we live. While exciting, AI innovation is often unpredictable. Tempering our enthusiasm is the sobering reality that rapid progress – while filled with opportunity – is never without its challenges.
The fascinating evolution of AI and self-learning algorithms have presented very different obstacles for teams in the security operations center (SOC), to combat adversaries. Freely available AI tools are assisting threat actors in creating synthetic identity-based attacks using fraudulent images, videos, audio, and more. This deception can be indistinguishable to humans – and exponentially raise the success rate for phishing and social engineering tactics. To defend, security teams should also be armed with AI-driven solutions for predictive analytics, advanced threat detection, investigation and response (TDIR), and exceptional improvements to workflow.
Before jumping headlong into the excitement and potential of AI, it’s our responsibility to evaluate the societal impacts. We must address ethical concerns and build robust security frameworks. AI is already revolutionizing industries, creating efficiencies and opening possibilities we never could have imagined just a few, short years ago. We’re only getting started and by proceeding with cautious optimism, we can remain vigilant to the obvious risks and avoid negative consequences, while still appreciating AI’s many benefits.
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Anthony Verna, SVP and GM, Cubic DTECH Mission Solutions
In the ever-evolving landscape of modern warfare, the role artificial intelligence (AI) places in dictating the trajectory of military operations must be emphasized. As we continue to see the complexities of an AI-accelerated battlespace intensify, AI combined with Machine Learning (ML) and advanced data processing have become indispensable to ensure the success of critical missions.
It’s also essential to recognize how vital next-generation tactical edge-based technologies are in providing decision advantage and how AI’s integration at the edge marks substantial advancement in military operations. The capability to process and interpret data instantaneously at the point of collection offers commanders prompt, actionable insights, facilitating rapid and well-informed decisions.
Modern operations demand immediate and precise data-to-decision capabilities to support mission-critical decisions at the swift pace of conflict today. This edge-based approach is crucial in denied, disrupted, intermittent, and limited (DDIL) environments where traditional communication channels may be compromised or unreliable.
As we celebrate AI Appreciation Day, let us acknowledge AI’s profound impact on our military capabilities, ensuring our forces are equipped with the most advanced technology to face the challenges of modern warfare and maintain a strategic advantage.
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Dave Hoekstra, Product Evangelist, Calabrio
AI Appreciation Day is a day to honor the past and present accomplishments of artificial intelligence (AI). AI is not a novel creation, but a product of decades of inquiry and invention. It improves our lives and efficiency, by allowing us to interact and obtain information quicker and easier than ever. Recent AI breakthroughs have opened up exciting opportunities in education and innovation, providing powerful tools to analyze data and act on insights like never before.
From early chatbots to advanced voicebots, contact center customers have interacted with AI technology. But the latest innovations in AI helps companies make sense of the data customers provide, like reviews, surveys or calls. Modern models can offer human and virtual agents ongoing feedback on customer interactions to improve them. Workstation copilots can also work with agents and help them find answers. While a helpful human touch will always be required in the contact center, these AI enhancements are becoming more and more essential for agents to perform their jobs effectively and to create a positive customer experience.
While the contact center is poised for significant improvements with AI, there are still important questions remaining: How do we make sure AI tools are impartial, transparent and accountable? How do we maintain a human-focused and cooperative method of customer service? These are some of the challenges we are addressing as we work towards a more advanced, AI-driven future in the contact center.
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Cris Grossmann, CEO and founder, Beekeeper
Each year, AI Appreciation Day serves as a reminder to embrace the transformative and powerful potential AI holds for frontline industries. The adoption of AI-powered tools by frontline businesses can provide managerial visibility, which is crucial for a more connected frontline workforce. Automated features like real-time evaluation of employee sentiment allow companies to proactively address concerns and prevent employee burnout. Utilizing AI to gauge employee sentiment not only improves retention and engagement but also unlocks new levels of operational efficiency that traditional methods cannot achieve.
No matter how many advancements in technology we make, AI will never be able to replace frontline workers. But it does have the power to enhance the experience of both frontline workers and managers through smart, people-first strategies.
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Javed Hasan, CEO and Co-founder, Lineaje
To meet modern business demands, developers often rely on open-source components to build AI-powered applications. It’s easy to see why, open source is quick and easily accessible. AI applications likely now comprise a significant portion of organizations’ software supply chains.
Despite AI software’s ability to transform businesses, it hasn’t been without consequences. Over Topics: Archive, VMBlog Info
