Exclusive Interview with Kevin Dallas, Chief Executive Officer, Enterprise DB

You interviewed more than 2000 senior executives across 13 countries about how they are planning for a genetic AI world. Why a genetic AI and why now?

Well, first of all there’s a large economic opportunity around AI. We forecast to be $16 trillion by 2030, and there’s about a trillion dollars that’s going to be spent in the area of AI over the next 12 months alone. So, every enterprise, every nation is investing in AI.

And when we say AI, there’s different types of AI. There’s generative AI, genetic AI, physical AI, and the time is now for that investment. You’re seeing it in the event today where many companies are making investments across the AI spectrum.

What is the data and AI sovereignty, and what happens when enterprises make it a mission-critical part of their strategy?

Well, to be able to actually run these intelligent applications, there is a need for a sovereign data and AI platform from EDB, Enterprise DB, our partners, NVIDIA, RedHat, and Supermicro. And with this new sovereign platform, we hope to deliver our customers the platform that they need to drive rapid innovation around these new AI applications.

Data sovereignty is gaining increased attention globally in the Middle East and the surrounding markets. How is EDB ensuring compliance, trust, and performance in your deployments?

Well, first of all, we’re finding that in this survey, it was very interesting, 95% of respondents are investing in a sovereign data and AI platform over the next three years.

And what they’re seeing is real benefits. They’re seeing two to three extra the velocity in terms of building out AI applications, and they’re seeing a five-fold increase in ROI. So, this is driving a lot of attention around this space.

Now, from an EDB perspective, we are delivering a standard sovereign data and AI platform that accelerates our customers to market. So, it’s a plug and play platform that resolves the security issues, compliance issues, and regulatory challenges that our customers have in a plug and play way.

How important is the UAE or the GCC region for EDB? Can you tell us about your corporate strategy in the GCC and how that aligns with the regional’s national agenda?

Well, what we found is that the biggest investments globally in sovereign data and AI are actually happening here in the region, in the UAE. There is a national vision that’s been set around open and around sovereign data and AI.

So, we’re very aligned in terms of our approach here. And the region, it’s very much like a Silicon Valley of sovereign data and AI, where there’s a lot of rich discussion around new use cases that our partners and our customers want to enable today versus tomorrow. So, it’s here and now in the region.

Looking ahead, six to 12 months from now, what is your message to the enterprises, governments, and other organizations who are considering or already on the AI journey?

I think in the next six to 12 months, focus on building your own sovereign data and AI platform. By doing this, it’s going to have a fivefold increase in your ROI and certainly increase your velocity to market.

But there is also, I think, a misconception. When we talk about sovereign, we talk about the benefit of secure, we talk about the benefit of compliance and regulatory requirements. Meeting those criteria, in some cases, can be viewed as slowing down the rate of innovations.

The opposite is true with our platform. By using a platform that has this capability built in, you’re able to accelerate your time to market.

How does EDB Postgres AI support data sovereignty in practice?

From a sovereign data and AI platform perspective, there are five key criteria that our customers need in the platform. One, open source based. This guarantees interoperability, access to talent, and it avoids vendor lock-in. This is something that even at a national level is important, open source based.

Second, the need to support multiple workloads, transactional, analytics, and AI workloads on one unified platform. Not three, but one. Third, there’s a need for a low-code, no-code application development environment. An environment that accelerates your time to market, an environment that democratizes AI for all.

So, you don’t have to be a developer, you can be a business decision maker and still create applications. Fourth, there needs to be a single pane glass view across the estate so you can monitor, secure, and drive compliance and meet those regulatory requirements across your entire estate. And then last, but by no means least, you need to be able to deploy in a hybrid fashion, meaning it’s not all about running workloads in the cloud.

You need to be able to run workloads on-prem, in the cloud, or in a dedicated system. So Sovereign is really those five things. It’s the ability to deploy in a hybrid manner.

It’s the ability to view your estate through a single pane of glass. It’s the ability to be able to run in a rich and dynamic low-code, no-code app environment, run multiple workloads, and of course, being open source.

Exclusive interview with Hetarth Patel, Vice President – Growth Markets (MEA, Americas, APAC), WebEngage

What role is AI playing in customer engagement in the region?

AI brings precision to moments that were previously handled with guesstimates. It identifies which customers are exploring something new, which ones are hesitating, and which ones may never return unless they’re nudged at the right time. That improves the experience without making users feel monitored or overwhelmed.

Across verticals, AI helps determine how frequently someone should be contacted, what format resonates with them, and when they’re most open to taking the next step. When communication follows the customer’s rhythm instead of the brand’s, loyalty strengthens naturally.

We are hearing more and more about contextual marketing. How would you define it in today’s Middle Eastern digital economy?

Contextual marketing in the Middle East is about recognising intent as it forms, not after the fact. Consumers in this region move quickly – comparison, consideration, and decision often happen in a single session. So brands need to respond to micro-signals in real time. When a platform can interpret these cues, the experience becomes smoother: relevant suggestions appear naturally, checkout journeys shorten, and customers feel understood without being overwhelmed. For businesses, this reduces wasted impressions and strengthens the quality of engagement. You convert the right people. The result is tighter spending, better retention, and a more predictable path to revenue.

How are customer engagement platforms evolving in the face of AI copilots and automations?

They’re becoming systems that support both momentum and oversight. Marketers in this region want recommendations, not replacements. The AI copilot element helps interpret data faster and flagging sudden behaviour spikes, suggesting audiences worth testing, or predicting where attention is drifting.

At the same time, automation has matured. Journeys can react to dozens of signals without manual input, and campaigns update themselves based on performance. This dual structure works well in markets like Saudi Arabia, where digital maturity is rising sharply. Teams get strategic clarity from the copilot, while automation handles the heavy lifting in the background.

Which technologies are proving most effective in helping GCC brands improve customer experience, ROI, and business outcomes?

The most effective setups are the ones where data moves freely. A Customer Data Platform(CDP) becomes powerful when it ingests live activity, loyalty signals, support tickets, and payment behaviour without friction. CRMs enrich that view with relationship history. Data lakes contribute long-term patterns that sharpen predictions.

What GCC brands are solving today is fragmentation. Teams get a single view of the user and can respond with confidence by connecting these systems cleanly. It also gives them the ability to test smaller ideas quickly instead of betting on broad, expensive campaigns. Better alignment across these tools results in higher ROI because every action is anchored in accurate context.

Across Saudi Arabia and the UAE, what improvements have you seen when brands move to AI-powered customer engagement and automation?

The most noticeable improvement is consistency. Brands no longer depend on campaign calendars to stay relevant, the system keeps the conversation going based on what users actually do. AI also cuts out the “one-size-fits-all” messages that used to frustrate customers across email, push, and in-app channels.

In sectors like airlines, grocery delivery, and financial services, we’ve seen repeat engagement rise simply because journeys adjust themselves. For example, a traveller exploring upgrade options receives timely details about availability rather than a generic newsletter. These small shifts accumulate and create clearer funnels, and a more efficient use of marketing time.

Could you share an example?

A recent example is NICE in Saudi Arabia, a brand with a large offline footprint that wanted deeper digital loyalty. Once their web and app activity were stitched together, the team could finally see how customers moved between browsing, carting, and store visits. That led to rethinking their journeys around intent instead of promotions.

As soon as they shifted to behaviour-led engagement – reactivating dormant shoppers, personalising recommendations, and automating recovery journeys – repeat visits rose sharply and engagement grew 148%. The improvement came from recognising micro-signals and responding early.

What is WebEngage’s long-term vision for the Middle East as brands shift from acquisition-heavy models to retention-driven growth?

Our long-term vision is to make retention operationally simple and strategically central. GCC businesses view retention as the engine that stabilises revenue. We’re building toward a future where engagement, loyalty, data governance, and service workflows sit within one connected layer.

This will allow brands to identify intent across channels, respond instantly, and measure outcomes with much greater accuracy. The goal is to help enterprises move from “sending messages” to designing relationships that last a lifetime.

How have you adapted in the face of these advancements?

Our competitive edge comes from how we operate, not what we claim. Scale, market rankings, and platform breadth matter, but they’re outcomes and not differentiators. What truly moves the needle for our customers in the Middle East is the way we build with flexible data architecture, a composable CDP that adapts to their systems rather than forcing a migration, and activation tools that work reliably at enterprise scale.

We’ve grown by treating engagement as an engineering problem rather than a marketing challenge. That mindset is what helps us scale. The idea is to make sure our fundamentals are strong enough to create the next set of milestones.

With regulations like PDPL and sector-specific frameworks in place, how essential is consent management for brands operating in the Middle East?

Consent management has become a structural requirement, especially as more industries digitise service delivery. It’s no longer about obtaining a checkbox, it’s about ensuring that user preferences flow across every system the brand uses – marketing, support, loyalty, and analytics.

In regulated categories, inconsistent consent handling can invalidate entire engagement programs. We address this by integrating with specialised consent tools so preferences update instantly across channels. Customers notice when brands respect these boundaries, and that strengthens long-term relationships.

What differentiates WebEngage in this region, and where do you see opportunities?

What sets us apart is our ability to adapt deeply to each organisation’s structure, whether it’s a fast-scaling marketplace or a highly regulated enterprise. The platform integrates into complex ecosystems without forcing data to move in unnatural ways.

Where we continue to evolve is governance, onboarding speed, and advanced modelling. The need for more precise controls and predictive capabilities increases as sectors like telecom, aviation, and financial services expand their digital footprints . We’re building tools that help teams act faster while meeting regulatory expectations with confidence.

What advancements can we expect from WebEngage in the next 12 months?

We’re now building on top of the foundations that already work well for our customers. The next phase is about reducing the effort needed to go from insight to action. After launching Insights CoPilot, we’re extending the ecosystem with Segmentation and Campaign CoPilot, and Governance CoPilot will follow. Each one is designed to shorten the path from understanding behaviour to acting on it with confidence.

In parallel, we’re deepening our machine-learning models so the system can recognise subtle behavioural shifts and adjust journeys with more nuance. The aim is to let the platform handle the operational complexity quietly in the background, while marketers focus on strategy, creativity, and the larger customer experience.

Exclusive interview with Amal Dimashki, Regional Director, MENAT, Turnitin.

1. What new teaching approaches are educators adopting today? Could you also share some of the strategies institutions are using to build AI literacy within their teaching community?

Education is experiencing a major transformation as artificial intelligence becomes more integrated learning experience. Educators are moving beyond traditional teaching methods and adopting dynamic, student-centered approaches. Blended learning, flipped classrooms, and project-based instruction are quickly becoming ‘the norm’, all supported by digital tools that personalize learning and foster deeper engagement.

A key shift is the rise of formative assessment practices. Continuous, adaptive feedback is changing how instructors support their students. AI platforms now provide real-time insights into individual progress, helping educators offer more tailored guidance. This not only improves learning outcomes but also encourages students to take better ownership of their educational journeys.

Moreover, Institutions are placing strong emphasis on building AI literacy. Professional development initiatives now cover technical skills, ethical considerations, prompt design, and the pedagogical shifts needed to use AI responsibly. Cross-functional committees ensure that policies, practices, and institutional values remain aligned.

AI literacy is being woven into curricula, so that both faculty and students hone the critical skills needed to engage purposefully with emerging technologies. Institutions are also working to promote equity by supporting underrepresented groups and ensuring broad access to essential AI tools.

Strategic partnerships with industry help keep education relevant to workforce needs. The most forward-thinking institutions see AI literacy as an ongoing commitment and foster a culture of  continuous learning.

• Has generative AI accelerated the shift away from traditional educational values? Do you believe reading and writing habits among students are being compromised more than in previous generations?

Generative AI has certainly advanced the pace of change, yet this transformation reflects evolution rather than erosion. The core values of education: critical thinking, creativity, integrity, and the pursuit of knowledge, remain steadfast. What is shifting is the way learners engage with these values.

Concerns about these changes are valid. The convenience of AI-generated content can tempt students to bypass the cognitive ‘creative’ effort essential for meaningful learning. Early research suggests that excessive reliance on AI may constrain creativity and weaken essential intellectual processes. Writing is not putting one word in front of another; it is the process of exploring thoughts, coping with the shades of meaning, and generating original ideas. Sidestepping this crucial process can hinder a student’s intellectual development.

The relationship between humanity  and technology has been an eternal dance, since every generation has faced challenges brought by new inventions. The difference today is the speed and scale of change. Students must now learn to read, write, and critically evaluate AI-generated material while recognizing bias and practicing ethical usage.

AI should not be seen as a threat to traditional educational values but as a tool  that can redefine and reinforce said values. The responsibility falls on educators to ensure that AI serves as a complement to authentic thinking, not a substitute for it. To achieve that, they should provide clear instruction and guidance, set expectations, and develop a robust foundation in both digital and human literacy.

• What new forms of academic misconduct have emerged with digital tools—such as contract cheating, essay mills, and AI-driven paraphrasing?

The digital era has introduced new dimensions of academic mischief (that being misconduct). While the underlying behaviors are nothing new, the tools that facilitate them have become advanced and easily accessible.

Contract cheating platforms now let students outsource assignments with the click of a button. Essay mills, powered by generative AI, now draft customized essays that even the most vigilant detectors, and educators cannot detect. Meanwhile, advanced paraphrasing tools can rewrite existing  content , sidestepping traditional plagiarism detectors with ease.

Collaboration, too, has taken on a new twist. With instant messaging and AI helpers, students can share answers in a matter of seconds or generate responses that they cleverly tweak to mask their true origins.

Tackling these challenges calls for more than detection tools. It requires a comprehensive strategy that combines technology with clear institutional policies, engaging education, and a campus culture rooted in integrity. The goal isn’t just to detect misconduct, but to make it less tempting by inspiring students to choose the ethical path to delivering original thoughts.

• Should educators have access to AI detection tools to identify cheating in the classroom? Given that Gen-Z is often more technologically savvy than their teachers, how can educators stay ahead?

Educators should have access to AI detection tools, while keeping in mind that such tools are but helpful guides- not mere flawless judges. The true value of these resources lies in the transparency and context they offer, helping to start a constructive conversation between educator and student.

At Turnitin, tools such as Turnitin Clarity allow educators to review the entire writing process from start to finish, including: early drafts and potential AI involvement instances. Such features help instructors set clearer expectations, offer more targeted feedback, and grade more fairly.

The availability of detection tools also serves as a deterrent, introducing a sense of uncertainty for students who might consider using AI improperly. However, detection alone is not enough. Educators should invite their students to have open discussions highlighting the importance of learning integrity, responsible AI use, and the value of an authentic learning experience.

As for keeping pace with tech-savvy students, educators need ongoing professional development, clear institutional policies, and supportive learning communities. Inviting students to these discussions can foster a sense of shared responsibility.

The ultimate goal is not to catch students but to guide them toward ethical, skill-building use of technology.

• What does the future of writing look like with the rise of AI tools like ChatGPT and Claude? Which types of assessments are naturally more resistant to AI-assisted cheating—such as practical projects, oral evaluations, or in-class writing?

The future of writing will be a partnership between human creativity and AI assistance. While AI can support idea generation, drafting, and editing, the essence of meaningful writing will always rest on originality, critical thinking, and the unique voice of the individual.

As AI becomes increasingly integrated into writing processes, assessment methods must adapt. The following types of assessments are more resilient to AI-assisted misconduct:

1. In-class writing assignments with restricted access to external tools and resources.
2. Oral assessments, including presentations and debates that test real-time thinking.
3. Hands-on projects that measure skills beyond AI’s reach.
4. Assessments focused on drafts and revisions to track progress over time.
5. Reflective tasks that require students to explain their thought process and decision-making.

These approaches prioritizes learning and process rather than the final product. They foster deeper learning by valuing originality, engagement, and genuine understanding.

• And finally, what’s the story behind Turnitin, and where do you see the platform heading next?

Turnitin began with a clear mission: to uphold academic learning in a rapidly changing educational landscape. Over time, it has grown from a plagiarism detection service into a comprehensive learning and integrity platform used and trusted by more than 16,000 institutions in more than 185 countries..

Our goal is to provide educators with the tools they need to promote authentic learning. This includes detecting misconduct, but it also advances transparency, fairness, and continuous improvement.

Looking ahead, Turnitin is enhancing its AI detection capabilities, developing inclusive data models and tools that reveal the entire learning process. We are committed to minimizing bias and supporting a diverse range of learners while ensuring our solutions remain accurate and equitable.

We are also strengthening partnerships across education, industry, and policy to support AI literacy and responsible use. As technology evolves, our focus stays the same: to bridge traditional academic values with new technologies, and to empower educators and students to move forward with integrity and purpose.